{
  "version": "1.0",
  "hub": "aifinhub",
  "generated_at": "2026-05-27T14:09:35.152Z",
  "total": 45,
  "base": "https://aifinhub.io/engines/",
  "engines": [
    {
      "slug": "agent-cost-envelope-calculator",
      "url": "https://aifinhub.io/engines/agent-cost-envelope-calculator.js",
      "types": "https://aifinhub.io/engines/agent-cost-envelope-calculator.d.ts",
      "exports": [
        "compute"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "model_id": {
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          "input_tokens_per_step",
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        ]
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              "tier": {
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              "inputUsdPerMToken": {
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              },
              "outputUsdPerMToken": {
                "type": "number"
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              "contextWindow": {
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          "steps": {
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            "items": {
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              "properties": {
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                "kind": {
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                  "enum": [
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                "inputCost": {
                  "type": "number"
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                  "type": "number"
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                  "type": "number"
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          "costPerLoop": {
            "type": "number"
          },
          "toolUseSubtotal": {
            "type": "number"
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          "convergenceCost": {
            "type": "number"
          },
          "costPerDay": {
            "type": "number"
          },
          "costPerMonth": {
            "type": "number"
          },
          "daysPerMonth": {
            "type": "integer"
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          "tokensPerLoop": {
            "type": "number"
          },
          "blendedUsdPer1KTokens": {
            "type": "number"
          },
          "withinBudget": {
            "type": "boolean"
          },
          "budgetUtilization": {
            "type": "number"
          }
        }
      },
      "example": {
        "tool": "agent_cost_envelope_calculator",
        "model_id": "claude-sonnet-4-6",
        "input_tokens_per_step": 4000,
        "output_tokens_per_step": 800,
        "steps_per_loop": 6,
        "convergence_check_pct": 50,
        "markets_per_day": 25,
        "target_monthly_usd": 500,
        "calendar_mode": "business"
      },
      "usage": "Client-side calculator. Open https://aifinhub.io/agent-cost-envelope-calculator/ and fill in the inputs; results render in-browser. Also importable as ES module from https://aifinhub.io/engines/agent-cost-envelope-calculator.js — call compute(input) with the JSON shape below."
    },
    {
      "slug": "agent-skill-tester",
      "url": "https://aifinhub.io/engines/agent-skill-tester.js",
      "types": "https://aifinhub.io/engines/agent-skill-tester.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
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          "skill_md": {
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          "sample_input_text": {
            "type": "string"
          },
          "model": {
            "type": "string"
          },
          "max_output_tokens": {
            "type": "integer"
          },
          "anthropic_api_key": {
            "type": "string"
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        "required": [
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          "skill_md",
          "sample_input_text",
          "model",
          "max_output_tokens",
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      "output_schema": {
        "type": "object",
        "properties": {
          "structured_output": {
            "type": "object"
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          "latency_ms": {
            "type": "number"
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          "input_tokens": {
            "type": "integer"
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          "output_tokens": {
            "type": "integer"
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          "cost_usd": {
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      },
      "example": {
        "tool": "agent_skill_tester",
        "skill_md": "# Skill: extract-10k-revenue\n\nReturn a JSON object with the reported total revenue...",
        "sample_input_text": "Excerpt from Form 10-K: ...",
        "model": "claude-opus-4-7",
        "max_output_tokens": 1024,
        "anthropic_api_key": "sk-ant-..."
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      "usage": "Client-side playground. Open https://aifinhub.io/agent-skill-tester/ and paste a SKILL.md + sample input + your Anthropic key. The key never leaves the browser."
    },
    {
      "slug": "backtest-overfitting-score",
      "url": "https://aifinhub.io/engines/backtest-overfitting-score.js",
      "types": "https://aifinhub.io/engines/backtest-overfitting-score.d.ts",
      "exports": [
        "compute",
        "computeBody"
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      "input_schema": {
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          "s": {
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          "max_combos": {
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          "seed": {
            "type": "number"
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        "required": [
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          "s",
          "max_combos",
          "seed"
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      },
      "output_schema": {
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        "properties": {
          "probability_of_backtest_overfitting": {
            "type": "number"
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          "deflated_sharpe_ratio": {
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          "expected_max_sharpe_null": {
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          "rank_consistency": {
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          "verdict": {
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            -0.004745,
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            0.016613,
            -0.013507,
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            -0.003244,
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          ]
        ],
        "names": [
          "config_1",
          "config_2",
          "config_3",
          "config_4",
          "config_5",
          "config_6",
          "config_7",
          "config_8"
        ]
      },
      "usage": "Client-side analyzer. Open https://aifinhub.io/backtest-overfitting-score/ and paste a returns CSV. Computes PBO + Deflated Sharpe in-browser."
    },
    {
      "slug": "batch-vs-realtime-cost-calculator",
      "url": "https://aifinhub.io/engines/batch-vs-realtime-cost-calculator.js",
      "types": "https://aifinhub.io/engines/batch-vs-realtime-cost-calculator.d.ts",
      "exports": [
        "compute"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "model_id": {
            "type": "string"
          },
          "jobs_per_day": {
            "type": "number"
          },
          "input_tokens_per_job": {
            "type": "number"
          },
          "output_tokens_per_job": {
            "type": "number"
          },
          "deadline_hours": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "model_id",
          "jobs_per_day",
          "input_tokens_per_job",
          "output_tokens_per_job",
          "deadline_hours"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "model": {
            "type": "object",
            "properties": {
              "id": {
                "type": "string"
              },
              "name": {
                "type": "string"
              },
              "provider": {
                "type": "string"
              },
              "tier": {
                "type": "string"
              },
              "inputUsdPerMToken": {
                "type": "number"
              },
              "outputUsdPerMToken": {
                "type": "number"
              },
              "contextWindow": {
                "type": "integer"
              }
            }
          },
          "realtimeCostPerDay": {
            "type": "number"
          },
          "batchCostPerDay": {
            "type": "number"
          },
          "effectiveCostPerDay": {
            "type": "number"
          },
          "savingsPerDay": {
            "type": "number"
          },
          "savingsPerMonth": {
            "type": "number"
          },
          "batchEligible": {
            "type": "boolean"
          },
          "usingBatch": {
            "type": "boolean"
          },
          "modeSuggestion": {
            "type": "string"
          },
          "providerComparison": {
            "type": "array",
            "items": {
              "type": "object",
              "properties": {
                "provider": {
                  "type": "string"
                },
                "model": {
                  "type": "object",
                  "properties": {
                    "id": {
                      "type": "string"
                    },
                    "name": {
                      "type": "string"
                    },
                    "provider": {
                      "type": "string"
                    },
                    "tier": {
                      "type": "string"
                    },
                    "inputUsdPerMToken": {
                      "type": "number"
                    },
                    "outputUsdPerMToken": {
                      "type": "number"
                    },
                    "contextWindow": {
                      "type": "integer"
                    }
                  }
                },
                "realtimeCostPerDay": {
                  "type": "number"
                },
                "batchCostPerDay": {
                  "type": "number"
                },
                "batchEligible": {
                  "type": "boolean"
                },
                "supportsBatch": {
                  "type": "boolean"
                },
                "batchSlaHours": {
                  "type": "number"
                }
              }
            }
          }
        }
      },
      "example": {
        "tool": "batch_vs_realtime_cost_calculator",
        "model_id": "claude-sonnet-4-6",
        "jobs_per_day": 10000,
        "input_tokens_per_job": 4000,
        "output_tokens_per_job": 800,
        "deadline_hours": 24
      },
      "usage": "Client-side calculator. Open https://aifinhub.io/batch-vs-realtime-cost-calculator/ and fill in the inputs; results render in-browser. Also importable as ES module from https://aifinhub.io/engines/batch-vs-realtime-cost-calculator.js — call compute(input) with the JSON shape below."
    },
    {
      "slug": "broker-api-comparator",
      "url": "https://aifinhub.io/engines/broker-api-comparator.js",
      "types": "https://aifinhub.io/engines/broker-api-comparator.d.ts",
      "exports": [
        "compute"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "require_options": {
            "type": "boolean"
          },
          "require_futures": {
            "type": "boolean"
          },
          "require_crypto": {
            "type": "boolean"
          },
          "require_mcp": {
            "type": "boolean"
          },
          "require_free_tier": {
            "type": "boolean"
          },
          "max_auth_complexity": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "require_options",
          "require_futures",
          "require_crypto",
          "require_mcp",
          "require_free_tier",
          "max_auth_complexity"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "filters": {
            "type": "object",
            "properties": {
              "requireOptions": {
                "type": "boolean"
              },
              "requireFutures": {
                "type": "boolean"
              },
              "requireCrypto": {
                "type": "boolean"
              },
              "requireMcp": {
                "type": "boolean"
              },
              "requireFreeTier": {
                "type": "boolean"
              },
              "maxAuthComplexity": {
                "type": "integer"
              }
            }
          },
          "results": {
            "type": "array",
            "items": {
              "type": "object",
              "properties": {
                "broker": {
                  "type": "object"
                },
                "score": {
                  "type": "integer"
                },
                "maxScore": {
                  "type": "integer"
                },
                "fits": {
                  "type": "boolean"
                },
                "failReasons": {
                  "type": "array",
                  "items": {
                    "type": "string"
                  }
                }
              }
            }
          },
          "fittingBrokers": {
            "type": "array",
            "items": {
              "type": "object"
            }
          }
        }
      },
      "example": {
        "tool": "broker-api-comparator",
        "require_options": false,
        "require_futures": false,
        "require_crypto": false,
        "require_mcp": false,
        "require_free_tier": false,
        "max_auth_complexity": 3
      },
      "usage": "Client-side broker API comparator. Open https://aifinhub.io/broker-api-comparator/ and set filters for asset classes, MCP availability, free tier, and max auth complexity. Ranked side-by-side of Alpaca, IBKR, Tradier, Schwab, Robinhood."
    },
    {
      "slug": "calibration-dojo",
      "url": "https://aifinhub.io/engines/calibration-dojo.js",
      "types": "https://aifinhub.io/engines/calibration-dojo.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "session_length_questions": {
            "type": "integer"
          },
          "difficulty": {
            "type": "string",
            "enum": [
              "easy",
              "medium",
              "hard"
            ]
          },
          "domain_filter": {
            "type": "string"
          }
        },
        "required": [
          "tool",
          "session_length_questions",
          "difficulty",
          "domain_filter"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "brier_score": {
            "type": "number"
          },
          "reliability_curve": {
            "type": "array",
            "items": {
              "type": "object",
              "properties": {
                "bucket_midpoint": {
                  "type": "number"
                },
                "observed_frequency": {
                  "type": "number"
                },
                "count": {
                  "type": "integer"
                }
              }
            }
          },
          "total_questions_answered": {
            "type": "integer"
          }
        }
      },
      "example": {
        "tool": "calibration_dojo",
        "session_length_questions": 20,
        "difficulty": "medium",
        "domain_filter": "general_knowledge"
      },
      "usage": "Client-side training game. Open https://aifinhub.io/calibration-dojo/ and answer binary forecasting questions. Brier score and reliability curve persist in localStorage."
    },
    {
      "slug": "cointegration-half-life-solver",
      "url": "https://aifinhub.io/engines/cointegration-half-life-solver.js",
      "types": "https://aifinhub.io/engines/cointegration-half-life-solver.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "lookback": {
            "type": "number"
          },
          "a": {
            "type": "array",
            "items": {
              "type": "number"
            }
          },
          "b": {
            "type": "array",
            "items": {
              "type": "number"
            }
          }
        },
        "required": [
          "tool",
          "lookback",
          "a",
          "b"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "beta": {
            "type": "number"
          },
          "intercept": {
            "type": "number"
          },
          "half_life_days": {
            "type": "number"
          },
          "adf_p_value": {
            "type": "number"
          },
          "r_squared": {
            "type": "number"
          }
        }
      },
      "example": {
        "tool": "cointegration-half-life-solver",
        "lookback": 252,
        "a": [
          0.01,
          0.02,
          -0.005,
          0.015,
          -0.01
        ],
        "b": [
          0.01,
          0.02,
          -0.005,
          0.015,
          -0.01
        ]
      },
      "usage": "Client-side calculator. Open https://aifinhub.io/cointegration-half-life-solver/ and fill in the inputs; results render in-browser."
    },
    {
      "slug": "correlation-matrix-visualizer",
      "url": "https://aifinhub.io/engines/correlation-matrix-visualizer.js",
      "types": "https://aifinhub.io/engines/correlation-matrix-visualizer.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "name": {
            "type": "string"
          },
          "values": {
            "type": "array",
            "items": {
              "type": "number"
            }
          }
        },
        "required": [
          "tool",
          "name",
          "values"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "correlation_matrix": {
            "type": "array",
            "items": {
              "type": "array",
              "items": {
                "type": "number"
              }
            }
          },
          "avg_abs_off_diagonal": {
            "type": "number"
          },
          "condition_number": {
            "type": "number"
          },
          "largest_eigenvalue": {
            "type": "number"
          },
          "explained_by_first_pc": {
            "type": "number"
          },
          "effective_n_strategies": {
            "type": "number"
          }
        }
      },
      "example": {
        "tool": "correlation-matrix-visualizer",
        "name": "",
        "values": [
          0.01,
          0.02,
          -0.005,
          0.015,
          -0.01
        ],
        "series": [
          {
            "name": "SPY",
            "values": [
              -0.012843,
              0.005562,
              -0.001332,
              0.001416,
              0.00507,
              0.006107,
              0.002444,
              0.004272,
              -0.002891,
              0.003178,
              0.00737,
              -0.004567,
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          {
            "name": "TLT",
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          },
          {
            "name": "GLD",
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          },
          {
            "name": "XLE",
            "values": [
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          }
        ]
      },
      "usage": "Client-side visualizer. Open https://aifinhub.io/correlation-matrix-visualizer/ and paste a wide-format returns CSV. Pearson correlation heatmap, eigenvalue spectrum, condition number, and effective-N render in-browser."
    },
    {
      "slug": "data-vendor-tco",
      "url": "https://aifinhub.io/engines/data-vendor-tco.js",
      "types": "https://aifinhub.io/engines/data-vendor-tco.d.ts",
      "exports": [
        "compute"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "needs_live": {
            "type": "boolean"
          },
          "needs_options": {
            "type": "boolean"
          },
          "needs_futures": {
            "type": "boolean"
          }
        },
        "required": [
          "tool",
          "needs_live",
          "needs_options",
          "needs_futures"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "per_vendor": {
            "type": "array",
            "items": {
              "type": "object",
              "properties": {
                "vendor": {
                  "type": "string"
                },
                "annual_cost_usd": {
                  "type": "number"
                },
                "notes": {
                  "type": "string"
                }
              }
            }
          },
          "ranked_cheapest_first": {
            "type": "array",
            "items": {
              "type": "string"
            }
          }
        }
      },
      "example": {
        "tool": "data-vendor-tco",
        "needs_live": false,
        "needs_options": false,
        "needs_futures": false
      },
      "usage": "Client-side comparator. Open https://aifinhub.io/data-vendor-tco/ and enter universe, bars, and history needs. Computes annual cost per vendor in-browser."
    },
    {
      "slug": "deflated-sharpe-ratio",
      "url": "https://aifinhub.io/engines/deflated-sharpe-ratio.js",
      "types": "https://aifinhub.io/engines/deflated-sharpe-ratio.d.ts",
      "exports": [
        "compute"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "observed_sr": {
            "type": "number"
          },
          "n": {
            "type": "number"
          },
          "skew": {
            "type": "number"
          },
          "kurt": {
            "type": "number"
          },
          "num_trials": {
            "type": "number"
          },
          "periods_per_year": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "observed_sr",
          "n",
          "skew",
          "kurt",
          "num_trials",
          "periods_per_year"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "deflated_sr": {
            "type": "number"
          },
          "psr": {
            "type": "number"
          },
          "max_expected_sr": {
            "type": "number"
          },
          "z_statistic": {
            "type": "number"
          }
        }
      },
      "example": {
        "tool": "deflated-sharpe-ratio",
        "observed_sr": 1.5,
        "n": 252,
        "skew": -0.4,
        "kurt": 3,
        "num_trials": 100,
        "periods_per_year": 252
      },
      "usage": "Client-side calculator. Open https://aifinhub.io/deflated-sharpe-ratio/ and fill in the inputs; results render in-browser."
    },
    {
      "slug": "drawdown-recovery-markov",
      "url": "https://aifinhub.io/engines/drawdown-recovery-markov.js",
      "types": "https://aifinhub.io/engines/drawdown-recovery-markov.d.ts",
      "exports": [
        "compute"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "monthly_sharpe": {
            "type": "number"
          },
          "monthly_skew": {
            "type": "number"
          },
          "monthly_excess_kurt": {
            "type": "number"
          },
          "recovery_threshold": {
            "type": "number"
          },
          "paths": {
            "type": "number"
          },
          "max_months": {
            "type": "number"
          },
          "seed": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "monthly_sharpe",
          "monthly_skew",
          "monthly_excess_kurt",
          "recovery_threshold",
          "paths",
          "max_months",
          "seed"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "median": {
            "type": "number"
          },
          "p25": {
            "type": "number"
          },
          "p75": {
            "type": "number"
          },
          "p95": {
            "type": "number"
          },
          "pct_recovered_in_12_mo": {
            "type": "number"
          }
        }
      },
      "example": {
        "tool": "drawdown-recovery-markov",
        "monthly_sharpe": 0.6,
        "monthly_skew": -0.3,
        "monthly_excess_kurt": 2,
        "recovery_threshold": 0.2,
        "paths": 2000,
        "max_months": 120,
        "seed": 42
      },
      "usage": "Client-side calculator. Open https://aifinhub.io/drawdown-recovery-markov/ and fill in the inputs; results render in-browser."
    },
    {
      "slug": "earnings-call-summarization-cost",
      "url": "https://aifinhub.io/engines/earnings-call-summarization-cost.js",
      "types": "https://aifinhub.io/engines/earnings-call-summarization-cost.d.ts",
      "exports": [
        "compute"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "tickers_per_quarter": {
            "type": "number"
          },
          "avg_transcript_tokens": {
            "type": "number"
          },
          "avg_summary_tokens": {
            "type": "number"
          },
          "cache_hit_rate": {
            "type": "number"
          },
          "summarization_attempts": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "tickers_per_quarter",
          "avg_transcript_tokens",
          "avg_summary_tokens",
          "cache_hit_rate",
          "summarization_attempts"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "per_stock_per_quarter": {
            "type": "number"
          },
          "per_stock_per_year": {
            "type": "number"
          },
          "per_year_total": {
            "type": "number"
          },
          "ranked": {
            "type": "array"
          }
        }
      },
      "example": {
        "tool": "earnings-call-summarization-cost",
        "tickers_per_quarter": 50,
        "avg_transcript_tokens": 15000,
        "avg_summary_tokens": 800,
        "cache_hit_rate": 0.5,
        "summarization_attempts": 1
      },
      "usage": "Client-side calculator. Open https://aifinhub.io/earnings-call-summarization-cost/ and fill in the inputs; results render in-browser."
    },
    {
      "slug": "efficient-frontier-builder",
      "url": "https://aifinhub.io/engines/efficient-frontier-builder.js",
      "types": "https://aifinhub.io/engines/efficient-frontier-builder.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "name": {
            "type": "string"
          },
          "returns": {
            "type": "array",
            "items": {
              "type": "number"
            }
          },
          "risk_free_annual": {
            "type": "number"
          },
          "steps": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "name",
          "returns",
          "risk_free_annual",
          "steps"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "min_variance_portfolio": {
            "type": "object",
            "properties": {
              "weights": {
                "type": "array",
                "items": {
                  "type": "number"
                }
              },
              "expected_return_annual": {
                "type": "number"
              },
              "volatility_annual": {
                "type": "number"
              },
              "sharpe_annual": {
                "type": "number"
              }
            }
          },
          "tangency_portfolio": {
            "type": "object",
            "properties": {
              "weights": {
                "type": "array",
                "items": {
                  "type": "number"
                }
              },
              "expected_return_annual": {
                "type": "number"
              },
              "volatility_annual": {
                "type": "number"
              },
              "sharpe_annual": {
                "type": "number"
              }
            }
          },
          "frontier_points": {
            "type": "array",
            "items": {
              "type": "object",
              "properties": {
                "expected_return_annual": {
                  "type": "number"
                },
                "volatility_annual": {
                  "type": "number"
                }
              }
            }
          }
        }
      },
      "example": {
        "tool": "efficient-frontier-builder",
        "name": "",
        "returns": [
          0.01,
          0.02,
          -0.005,
          0.015,
          -0.01
        ],
        "risk_free_annual": 0.04,
        "steps": 60,
        "assets": [
          {
            "name": "US Equities",
            "returns": [
              -0.026084,
              -0.009339,
              0.022423,
              0.024265,
              -0.00407,
              -0.032333,
              -0.00286,
              -0.013928,
              0.011828,
              0.020775,
              0.011517,
              0.006625,
              0.003477,
              0.00601,
              -0.008305,
              -0.01288,
              -0.013881,
              0.015359,
              0.011678,
              -0.016119,
              -0.003055,
              0.010377,
              -0.010538,
              -0.022867,
              0.001126,
              0.004041,
              -0.019115,
              -0.020235,
              0.016568,
              -0.005748,
              -0.011775,
              0.032105,
              0.002526,
              -0.000716,
              0.021207,
              0.005723,
              -0.002615,
              0.014075,
              0.017308,
              0.012199,
              0.014812,
              -0.024036,
              -0.007398,
              -0.009666,
              0.034898,
              -0.00267,
              -0.008985,
              0.013844,
              0.006004,
              -0.012636,
              0.00792,
              -0.001344,
              -0.033702,
              0.010719,
              -0.009275,
              -0.002554,
              -0.001274,
              -0.004542,
              0.009619,
              0.003683,
              0.00918,
              0.008551,
              0.003124,
              -0.04027,
              -0.004669,
              0.022377,
              0.027628,
              0.008361,
              0.000285,
              -0.010508,
              0.010258,
              -0.003251,
              0.015045,
              -0.007165,
              -0.004979,
              0.020983,
              0.008768,
              0.012502,
              0.000001,
              0.020556,
              -0.021939,
              0.018329,
              -0.001071,
              -0.004927,
              0.005116,
              -0.019207,
              -0.01628,
              -0.016438,
              -0.013193,
              0.011414,
              0.005628,
              -0.02627,
              -0.030247,
              0.015763,
              -0.006258,
              0.023799
            ]
          },
          {
            "name": "Intl Equities",
            "returns": [
              -0.01789,
              -0.016342,
              0.011449,
              0.013527,
              0.002128,
              -0.000148,
              -0.003973,
              -0.005458,
              0.004932,
              0.012879,
              0.00009,
              -0.004105,
              0.004944,
              0.005493,
              0.012637,
              0.016019,
              -0.011988,
              0.012194,
              0.008298,
              -0.00734,
              -0.002411,
              -0.01554,
              -0.003597,
              -0.026939,
              0.014074,
              0.001976,
              -0.001698,
              0.000053,
              -0.002408,
              0.015902,
              -0.007393,
              0.009357,
              -0.004008,
              0.001894,
              0.013792,
              -0.000589,
              0.00913,
              0.007222,
              0.003309,
              0.016436,
              0.006723,
              -0.009458,
              -0.000424,
              -0.036102,
              0.020203,
              -0.001423,
              0.006391,
              0.0019,
              -0.011855,
              -0.008596,
              -0.000051,
              -0.020171,
              -0.002348,
              0.008743,
              0.002821,
              0.013084,
              0.024959,
              0.005673,
              -0.01992,
              0.01727,
              0.007925,
              0.025043,
              0.019246,
              -0.018409,
              0.007818,
              -0.012283,
              0.005164,
              -0.000647,
              0.000651,
              0.016975,
              -0.016459,
              0.010047,
              0.011959,
              0.008598,
              0.008194,
              -0.020397,
              0.016703,
              0.000529,
              0.008447,
              0.008478,
              -0.025,
              0.011464,
              0.007115,
              -0.003013,
              -0.003825,
              -0.030416,
              -0.001629,
              -0.007607,
              -0.009038,
              -0.011127,
              0.004869,
              -0.014431,
              -0.003256,
              0.011009,
              -0.000182,
              0.030479
            ]
          },
          {
            "name": "Aggregate Bonds",
            "returns": [
              0.003383,
              -0.005414,
              -0.000468,
              0.003312,
              0.001429,
              0.005737,
              -0.005907,
              -0.000994,
              -0.002542,
              0.004991,
              -0.004859,
              0.00201,
              0.001642,
              0.000324,
              -0.003314,
              -0.002803,
              0.00019,
              -0.000551,
              -0.007022,
              -0.000428,
              -0.001826,
              0.005103,
              0.00709,
              -0.002827,
              -0.002037,
              0.00013,
              0.004804,
              0.005379,
              0.002667,
              -0.00091,
              -0.003758,
              -0.007383,
              0.001706,
              0.000864,
              0.005508,
              -0.007142,
              0.004368,
              -0.004738,
              -0.007385,
              0.001689,
              -0.004507,
              -0.000357,
              -0.000415,
              0.005325,
              0.004308,
              -0.000416,
              0.00277,
              -0.007876,
              0.001166,
              -0.006418,
              -0.005774,
              -0.001906,
              0.0091,
              -0.002563,
              -0.002665,
              -0.001689,
              -0.005174,
              -0.003989,
              0.00354,
              0.001622,
              0.001807,
              -0.008514,
              0.007035,
              0.010241,
              -0.001968,
              -0.000503,
              -0.005232,
              -0.000794,
              0.009881,
              -0.001286,
              0.006395,
              -0.002523,
              0.004048,
              0.00066,
              -0.003002,
              0.003417,
              -0.000537,
              -0.00362,
              0.003066,
              -0.005197,
              -0.00165,
              -0.005964,
              -0.001629,
              -0.007396,
              -0.003472,
              -0.001102,
              0.005919,
              -0.000683,
              0.001568,
              -0.000526,
              0.004182,
              -0.002288,
              0.008541,
              -0.002672,
              0.00223,
              -0.000601
            ]
          },
          {
            "name": "Commodities",
            "returns": [
              0.010693,
              -0.014358,
              0.001653,
              0.026449,
              0.036177,
              -0.024715,
              -0.01015,
              0.003149,
              -0.004191,
              0.008498,
              0.006201,
              0.006443,
              0.007429,
              0.001224,
              0.008414,
              0.004634,
              -0.026895,
              0.014692,
              -0.009684,
              0.003576,
              0.01979,
              -0.013675,
              0.006075,
              -0.006749,
              0.017848,
              -0.024232,
              0.006072,
              -0.00843,
              -0.005465,
              -0.010567,
              0.005011,
              -0.00479,
              -0.002642,
              -0.006506,
              0.005338,
              -0.015151,
              -0.010684,
              -0.02011,
              -0.017681,
              -0.01455,
              -0.014944,
              0.003162,
              0.015392,
              -0.015318,
              0.009544,
              -0.000737,
              -0.01655,
              -0.003292,
              0.013558,
              0.007808,
              -0.010701,
              0.006641,
              -0.014237,
              -0.022369,
              0.011828,
              -0.004968,
              0.008261,
              0.019919,
              0.00125,
              -0.009036,
              -0.003743,
              0.00962,
              -0.012011,
              0.025194,
              0.006848,
              0.037353,
              0.011328,
              -0.021955,
              -0.00327,
              -0.007504,
              -0.0303,
              0.008215,
              -0.000348,
              -0.012391,
              0.007949,
              -0.002983,
              -0.013971,
              -0.009568,
              -0.009759,
              -0.009918,
              -0.013714,
              -0.022232,
              -0.013597,
              0.016836,
              -0.003036,
              -0.004977,
              -0.024345,
              -0.024586,
              0.002842,
              0.014054,
              0.005342,
              -0.004593,
              -0.010622,
              -0.018985,
              0.012889,
              0.014289
            ]
          }
        ]
      },
      "usage": "Client-side calculator. Open https://aifinhub.io/efficient-frontier-builder/ and paste a multi-asset returns CSV. Markowitz frontier + min-var + tangency portfolios render in-browser."
    },
    {
      "slug": "execution-simulator",
      "url": "https://aifinhub.io/engines/execution-simulator.js",
      "types": "https://aifinhub.io/engines/execution-simulator.d.ts",
      "exports": [
        "compute"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "side": {
            "type": "string"
          },
          "order_size": {
            "type": "number"
          },
          "adv": {
            "type": "number"
          },
          "spread_bps": {
            "type": "number"
          },
          "daily_vol_pct": {
            "type": "number"
          },
          "participation_pct": {
            "type": "number"
          },
          "latency_ms": {
            "type": "number"
          },
          "latency_jitter_ms": {
            "type": "number"
          },
          "ref_price": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "side",
          "order_size",
          "adv",
          "spread_bps",
          "daily_vol_pct",
          "participation_pct",
          "latency_ms",
          "latency_jitter_ms",
          "ref_price"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "side": {
            "type": "string",
            "enum": [
              "buy",
              "sell"
            ]
          },
          "permanentBps": {
            "type": "number"
          },
          "temporaryBps": {
            "type": "number"
          },
          "halfSpreadBps": {
            "type": "number"
          },
          "totalBps": {
            "type": "number"
          },
          "totalDollars": {
            "type": "number"
          },
          "notionalUsd": {
            "type": "number"
          },
          "durationMinutes": {
            "type": "number"
          },
          "latencyDriftBps": {
            "type": "number"
          },
          "latencyDriftWorstBps": {
            "type": "number"
          }
        }
      },
      "example": {
        "tool": "execution-simulator",
        "side": "buy",
        "order_size": 50000,
        "adv": 5000000,
        "spread_bps": 8,
        "daily_vol_pct": 2,
        "participation_pct": 10,
        "latency_ms": 150,
        "latency_jitter_ms": 40,
        "ref_price": 100
      },
      "usage": "Client-side execution simulator. Open https://aifinhub.io/execution-simulator/ and configure order size, ADV, spread, volatility, participation rate, and latency. Square-root permanent impact + linear temporary impact + latency drift are computed in-browser."
    },
    {
      "slug": "fallback-chain-simulator",
      "url": "https://aifinhub.io/engines/fallback-chain-simulator.js",
      "types": "https://aifinhub.io/engines/fallback-chain-simulator.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "provider_id": {
            "type": "string"
          },
          "model_id": {
            "type": "string"
          },
          "rate_429": {
            "type": "number"
          },
          "p99_latency_ms": {
            "type": "number"
          },
          "deadline_ms": {
            "type": "number"
          },
          "input_tokens": {
            "type": "number"
          },
          "output_tokens": {
            "type": "number"
          },
          "trials": {
            "type": "number"
          },
          "seed": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "provider_id",
          "model_id",
          "rate_429",
          "p99_latency_ms",
          "deadline_ms",
          "input_tokens",
          "output_tokens",
          "trials",
          "seed"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "providers": {
            "type": "array",
            "items": {
              "type": "object",
              "properties": {
                "id": {
                  "type": "string"
                },
                "name": {
                  "type": "string"
                },
                "models": {
                  "type": "array",
                  "items": {
                    "type": "string"
                  }
                }
              }
            }
          },
          "hint": {
            "type": "string"
          }
        }
      },
      "example": {
        "tool": "fallback_chain_simulator",
        "provider_id": "",
        "model_id": "",
        "rate_429": 0,
        "p99_latency_ms": 0,
        "deadline_ms": 0,
        "input_tokens": 0,
        "output_tokens": 0,
        "trials": 1000,
        "seed": 1
      },
      "usage": "Client-side calculator. Open https://aifinhub.io/fallback-chain-simulator/ and fill in the inputs; results render in-browser. Also importable as ES module from https://aifinhub.io/engines/fallback-chain-simulator.js — call compute(input) with the JSON shape below."
    },
    {
      "slug": "finance-mcp-directory",
      "url": "https://aifinhub.io/engines/finance-mcp-directory.js",
      "types": "https://aifinhub.io/engines/finance-mcp-directory.d.ts",
      "exports": [
        "compute"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "filter_by_venue": {
            "type": "string"
          },
          "filter_by_scope": {
            "type": "string"
          },
          "min_security_grade": {
            "type": "string",
            "enum": [
              "A",
              "B",
              "C",
              "D",
              "F"
            ]
          }
        },
        "required": [
          "tool"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "servers": {
            "type": "array",
            "items": {
              "type": "object",
              "properties": {
                "name": {
                  "type": "string"
                },
                "venue": {
                  "type": "string"
                },
                "scopes": {
                  "type": "array",
                  "items": {
                    "type": "string"
                  }
                },
                "transport": {
                  "type": "string"
                },
                "auth": {
                  "type": "string"
                },
                "idempotency": {
                  "type": "boolean"
                },
                "security_grade": {
                  "type": "string"
                },
                "source_url": {
                  "type": "string"
                }
              }
            }
          }
        }
      },
      "example": {
        "tool": "finance_mcp_directory",
        "filter_by_venue": "alpaca",
        "filter_by_scope": "market_data",
        "min_security_grade": "B"
      },
      "usage": "Static directory. Open https://aifinhub.io/finance-mcp-directory/ to browse MCP servers by venue, scope, and security grade. Read-only; no inputs required for browsing."
    },
    {
      "slug": "financial-document-token-estimator",
      "url": "https://aifinhub.io/engines/financial-document-token-estimator.js",
      "types": "https://aifinhub.io/engines/financial-document-token-estimator.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "mode": {
            "type": "string"
          },
          "archetype_id": {
            "type": "string"
          },
          "output_tokens": {
            "type": "number"
          },
          "peers": {
            "type": "number"
          },
          "cache_hit_rate": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "mode",
          "archetype_id",
          "output_tokens",
          "peers",
          "cache_hit_rate"
        ]
      },
      "output_schema": {
        "type": "array",
        "description": "One row per model in the rate table.",
        "items": {
          "type": "object",
          "properties": {
            "model": {
              "type": "object"
            },
            "inputTokens": {
              "type": "integer"
            },
            "cacheReadTokens": {
              "type": "integer"
            },
            "outputTokens": {
              "type": "integer"
            },
            "onePassCost": {
              "type": "number"
            },
            "synthesisCost": {
              "type": "number"
            },
            "synthesisInputTokens": {
              "type": "integer"
            },
            "fitsInContext": {
              "type": "boolean"
            }
          }
        }
      },
      "example": {
        "tool": "financial_document_token_estimator",
        "mode": "archetype",
        "archetype_id": "10-k",
        "output_tokens": 1000,
        "peers": 0,
        "cache_hit_rate": 0
      },
      "usage": "Client-side calculator. Open https://aifinhub.io/financial-document-token-estimator/ and fill in the inputs; results render in-browser. Also importable as ES module from https://aifinhub.io/engines/financial-document-token-estimator.js — call compute(input) with the JSON shape below."
    },
    {
      "slug": "forecast-scoring-sandbox",
      "url": "https://aifinhub.io/engines/forecast-scoring-sandbox.js",
      "types": "https://aifinhub.io/engines/forecast-scoring-sandbox.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "n_bins": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "n_bins"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "brier": {
            "type": "object",
            "properties": {
              "brier": {
                "type": "number"
              },
              "reliability": {
                "type": "number"
              },
              "resolution": {
                "type": "number"
              },
              "uncertainty": {
                "type": "number"
              },
              "baseRate": {
                "type": "number"
              },
              "count": {
                "type": "integer"
              },
              "binsUsed": {
                "type": "integer"
              }
            }
          },
          "logLoss": {
            "type": "number"
          },
          "bins": {
            "type": "array",
            "items": {
              "type": "object",
              "properties": {
                "index": {
                  "type": "integer"
                },
                "lower": {
                  "type": "number"
                },
                "upper": {
                  "type": "number"
                },
                "mid": {
                  "type": "number"
                },
                "meanPred": {
                  "type": "number"
                },
                "observedFreq": {
                  "type": "number"
                },
                "count": {
                  "type": "integer"
                }
              }
            }
          }
        }
      },
      "example": {
        "tool": "forecast_scoring_sandbox",
        "n_bins": 10,
        "forecasts": [
          {
            "prob": 0.6116,
            "outcome": 1
          },
          {
            "prob": 0.2413,
            "outcome": 0
          },
          {
            "prob": 0.5151,
            "outcome": 1
          },
          {
            "prob": 0.7806,
            "outcome": 1
          },
          {
            "prob": 0.7085,
            "outcome": 1
          },
          {
            "prob": 0.9285,
            "outcome": 1
          },
          {
            "prob": 0.4567,
            "outcome": 0
          },
          {
            "prob": 0.5556,
            "outcome": 1
          },
          {
            "prob": 0.0636,
            "outcome": 0
          },
          {
            "prob": 0.2901,
            "outcome": 0
          },
          {
            "prob": 0.3226,
            "outcome": 0
          },
          {
            "prob": 0.3229,
            "outcome": 1
          },
          {
            "prob": 0.5248,
            "outcome": 1
          },
          {
            "prob": 0.8689,
            "outcome": 1
          },
          {
            "prob": 0.1544,
            "outcome": 1
          },
          {
            "prob": 0.531,
            "outcome": 1
          },
          {
            "prob": 0.6319,
            "outcome": 1
          },
          {
            "prob": 0.7363,
            "outcome": 1
          },
          {
            "prob": 0.0861,
            "outcome": 0
          },
          {
            "prob": 0.3397,
            "outcome": 1
          },
          {
            "prob": 0.4632,
            "outcome": 0
          },
          {
            "prob": 0.7156,
            "outcome": 0
          },
          {
            "prob": 0.6064,
            "outcome": 1
          },
          {
            "prob": 0.4834,
            "outcome": 1
          },
          {
            "prob": 0.4628,
            "outcome": 0
          },
          {
            "prob": 0.6358,
            "outcome": 0
          },
          {
            "prob": 0.4015,
            "outcome": 0
          },
          {
            "prob": 0.5665,
            "outcome": 1
          },
          {
            "prob": 0.5495,
            "outcome": 0
          },
          {
            "prob": 0.8171,
            "outcome": 1
          },
          {
            "prob": 0.7797,
            "outcome": 1
          },
          {
            "prob": 0.6885,
            "outcome": 0
          },
          {
            "prob": 0.4069,
            "outcome": 1
          },
          {
            "prob": 0.6873,
            "outcome": 1
          },
          {
            "prob": 0.477,
            "outcome": 0
          },
          {
            "prob": 0.202,
            "outcome": 0
          },
          {
            "prob": 0.0545,
            "outcome": 0
          },
          {
            "prob": 0.83,
            "outcome": 1
          },
          {
            "prob": 0.644,
            "outcome": 1
          },
          {
            "prob": 0.8006,
            "outcome": 1
          },
          {
            "prob": 0.7005,
            "outcome": 1
          },
          {
            "prob": 0.3634,
            "outcome": 1
          },
          {
            "prob": 0.2142,
            "outcome": 0
          },
          {
            "prob": 0.439,
            "outcome": 1
          },
          {
            "prob": 0.4753,
            "outcome": 1
          },
          {
            "prob": 0.4507,
            "outcome": 0
          },
          {
            "prob": 0.5532,
            "outcome": 0
          },
          {
            "prob": 0.5839,
            "outcome": 1
          },
          {
            "prob": 0.3468,
            "outcome": 0
          },
          {
            "prob": 0.4419,
            "outcome": 1
          },
          {
            "prob": 0.4895,
            "outcome": 0
          },
          {
            "prob": 0.6959,
            "outcome": 1
          },
          {
            "prob": 0.4164,
            "outcome": 0
          },
          {
            "prob": 0.1464,
            "outcome": 0
          },
          {
            "prob": 0.6264,
            "outcome": 0
          },
          {
            "prob": 0.6437,
            "outcome": 0
          },
          {
            "prob": 0.097,
            "outcome": 0
          },
          {
            "prob": 0.1371,
            "outcome": 0
          },
          {
            "prob": 0.7351,
            "outcome": 1
          },
          {
            "prob": 0.2478,
            "outcome": 0
          },
          {
            "prob": 0.3712,
            "outcome": 1
          },
          {
            "prob": 0.086,
            "outcome": 0
          },
          {
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            "outcome": 0
          },
          {
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            "outcome": 0
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            "outcome": 1
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          {
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            "outcome": 1
          },
          {
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            "outcome": 0
          },
          {
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            "outcome": 1
          },
          {
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            "outcome": 0
          },
          {
            "prob": 0.8722,
            "outcome": 1
          },
          {
            "prob": 0.4556,
            "outcome": 0
          },
          {
            "prob": 0.907,
            "outcome": 0
          },
          {
            "prob": 0.7428,
            "outcome": 0
          },
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            "outcome": 0
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            "outcome": 0
          },
          {
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            "outcome": 1
          },
          {
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            "outcome": 1
          },
          {
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            "outcome": 1
          },
          {
            "prob": 0.9079,
            "outcome": 1
          },
          {
            "prob": 0.5081,
            "outcome": 1
          },
          {
            "prob": 0.913,
            "outcome": 1
          },
          {
            "prob": 0.7671,
            "outcome": 1
          },
          {
            "prob": 0.5628,
            "outcome": 1
          },
          {
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            "outcome": 0
          },
          {
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            "outcome": 1
          },
          {
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            "outcome": 0
          },
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            "outcome": 0
          },
          {
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            "outcome": 1
          },
          {
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            "outcome": 0
          },
          {
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            "outcome": 0
          },
          {
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            "outcome": 0
          },
          {
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            "outcome": 0
          },
          {
            "prob": 0.2513,
            "outcome": 0
          },
          {
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            "outcome": 1
          },
          {
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            "outcome": 1
          },
          {
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            "outcome": 1
          },
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            "outcome": 0
          },
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            "outcome": 1
          },
          {
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            "outcome": 1
          },
          {
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            "outcome": 0
          },
          {
            "prob": 0.7694,
            "outcome": 1
          },
          {
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            "outcome": 1
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            "outcome": 1
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            "outcome": 0
          },
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            "outcome": 0
          },
          {
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            "outcome": 0
          },
          {
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            "outcome": 1
          },
          {
            "prob": 0.382,
            "outcome": 1
          },
          {
            "prob": 0.2754,
            "outcome": 0
          },
          {
            "prob": 0.8545,
            "outcome": 1
          },
          {
            "prob": 0.0979,
            "outcome": 0
          },
          {
            "prob": 0.8213,
            "outcome": 1
          },
          {
            "prob": 0.7177,
            "outcome": 1
          },
          {
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            "outcome": 1
          },
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            "outcome": 0
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            "outcome": 0
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          {
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            "outcome": 1
          },
          {
            "prob": 0.7734,
            "outcome": 0
          },
          {
            "prob": 0.2254,
            "outcome": 1
          },
          {
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            "outcome": 1
          },
          {
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            "outcome": 1
          },
          {
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            "outcome": 0
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            "outcome": 0
          },
          {
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            "outcome": 0
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            "outcome": 0
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            "outcome": 0
          },
          {
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            "outcome": 0
          },
          {
            "prob": 0.3697,
            "outcome": 0
          },
          {
            "prob": 0.1944,
            "outcome": 0
          },
          {
            "prob": 0.537,
            "outcome": 1
          },
          {
            "prob": 0.6084,
            "outcome": 0
          },
          {
            "prob": 0.4809,
            "outcome": 1
          },
          {
            "prob": 0.0937,
            "outcome": 1
          },
          {
            "prob": 0.468,
            "outcome": 0
          },
          {
            "prob": 0.7695,
            "outcome": 1
          },
          {
            "prob": 0.075,
            "outcome": 0
          },
          {
            "prob": 0.6921,
            "outcome": 0
          },
          {
            "prob": 0.6378,
            "outcome": 0
          },
          {
            "prob": 0.3382,
            "outcome": 0
          },
          {
            "prob": 0.738,
            "outcome": 0
          },
          {
            "prob": 0.443,
            "outcome": 0
          },
          {
            "prob": 0.5461,
            "outcome": 0
          },
          {
            "prob": 0.8276,
            "outcome": 0
          },
          {
            "prob": 0.4662,
            "outcome": 1
          },
          {
            "prob": 0.1732,
            "outcome": 0
          },
          {
            "prob": 0.4532,
            "outcome": 0
          },
          {
            "prob": 0.5243,
            "outcome": 0
          },
          {
            "prob": 0.2983,
            "outcome": 0
          },
          {
            "prob": 0.7292,
            "outcome": 0
          },
          {
            "prob": 0.5018,
            "outcome": 1
          },
          {
            "prob": 0.1507,
            "outcome": 1
          },
          {
            "prob": 0.8793,
            "outcome": 1
          },
          {
            "prob": 0.9044,
            "outcome": 0
          },
          {
            "prob": 0.572,
            "outcome": 1
          },
          {
            "prob": 0.7079,
            "outcome": 0
          },
          {
            "prob": 0.655,
            "outcome": 1
          },
          {
            "prob": 0.1483,
            "outcome": 0
          },
          {
            "prob": 0.8662,
            "outcome": 1
          },
          {
            "prob": 0.7007,
            "outcome": 0
          },
          {
            "prob": 0.198,
            "outcome": 0
          },
          {
            "prob": 0.6565,
            "outcome": 1
          },
          {
            "prob": 0.5257,
            "outcome": 0
          },
          {
            "prob": 0.8426,
            "outcome": 1
          },
          {
            "prob": 0.0648,
            "outcome": 0
          },
          {
            "prob": 0.7416,
            "outcome": 1
          },
          {
            "prob": 0.5789,
            "outcome": 1
          },
          {
            "prob": 0.943,
            "outcome": 1
          },
          {
            "prob": 0.2844,
            "outcome": 0
          },
          {
            "prob": 0.1861,
            "outcome": 0
          },
          {
            "prob": 0.4199,
            "outcome": 1
          },
          {
            "prob": 0.6753,
            "outcome": 1
          },
          {
            "prob": 0.5781,
            "outcome": 0
          },
          {
            "prob": 0.4762,
            "outcome": 1
          },
          {
            "prob": 0.4191,
            "outcome": 1
          },
          {
            "prob": 0.6264,
            "outcome": 0
          },
          {
            "prob": 0.4104,
            "outcome": 0
          },
          {
            "prob": 0.8167,
            "outcome": 1
          },
          {
            "prob": 0.765,
            "outcome": 0
          },
          {
            "prob": 0.9276,
            "outcome": 1
          },
          {
            "prob": 0.6712,
            "outcome": 1
          },
          {
            "prob": 0.7273,
            "outcome": 0
          },
          {
            "prob": 0.1366,
            "outcome": 0
          },
          {
            "prob": 0.1657,
            "outcome": 0
          },
          {
            "prob": 0.6893,
            "outcome": 0
          },
          {
            "prob": 0.22,
            "outcome": 1
          },
          {
            "prob": 0.5081,
            "outcome": 1
          },
          {
            "prob": 0.8771,
            "outcome": 1
          },
          {
            "prob": 0.477,
            "outcome": 1
          },
          {
            "prob": 0.2583,
            "outcome": 1
          },
          {
            "prob": 0.0835,
            "outcome": 0
          },
          {
            "prob": 0.9217,
            "outcome": 1
          },
          {
            "prob": 0.1064,
            "outcome": 0
          },
          {
            "prob": 0.797,
            "outcome": 1
          },
          {
            "prob": 0.4639,
            "outcome": 0
          },
          {
            "prob": 0.4387,
            "outcome": 0
          },
          {
            "prob": 0.7163,
            "outcome": 1
          },
          {
            "prob": 0.9031,
            "outcome": 1
          },
          {
            "prob": 0.1449,
            "outcome": 0
          },
          {
            "prob": 0.0834,
            "outcome": 0
          },
          {
            "prob": 0.8509,
            "outcome": 1
          }
        ]
      },
      "usage": "Client-side calculator. Open https://aifinhub.io/forecast-scoring-sandbox/ and fill in the inputs; results render in-browser. Also importable as ES module from https://aifinhub.io/engines/forecast-scoring-sandbox.js — call compute(input) with the JSON shape below."
    },
    {
      "slug": "ftc-vs-nlt-regulatory-cost",
      "url": "https://aifinhub.io/engines/ftc-vs-nlt-regulatory-cost.js",
      "types": "https://aifinhub.io/engines/ftc-vs-nlt-regulatory-cost.d.ts",
      "exports": [
        "compute"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "data_volume_tier": {
            "type": "number"
          },
          "processing_complexity": {
            "type": "number"
          },
          "hourly_rate": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "data_volume_tier",
          "processing_complexity",
          "hourly_rate"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "lowest_friction": {
            "type": "string"
          },
          "monthly_cost_usd": {
            "type": "number"
          },
          "annual_cost_usd": {
            "type": "number"
          },
          "ranked": {
            "type": "array"
          }
        }
      },
      "example": {
        "tool": "ftc-vs-nlt-regulatory-cost",
        "data_volume_tier": 2,
        "processing_complexity": 1.5,
        "hourly_rate": 120
      },
      "usage": "Client-side calculator. Open https://aifinhub.io/ftc-vs-nlt-regulatory-cost/ and fill in the inputs; results render in-browser."
    },
    {
      "slug": "hallucination-detector",
      "url": "https://aifinhub.io/engines/hallucination-detector.js",
      "types": "https://aifinhub.io/engines/hallucination-detector.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "source": {
            "type": "string"
          },
          "output": {
            "type": "string"
          }
        },
        "required": [
          "tool",
          "source",
          "output"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "numeric_claims": {
            "type": "array",
            "items": {
              "type": "object",
              "properties": {
                "claim": {
                  "type": "string"
                },
                "value": {
                  "type": "number"
                },
                "supported": {
                  "type": "boolean"
                },
                "source_quote": {
                  "type": "string"
                }
              }
            }
          },
          "unsupported_fraction": {
            "type": "number"
          },
          "verdict": {
            "type": "string"
          }
        }
      },
      "example": {
        "tool": "hallucination-detector",
        "source": "",
        "output": ""
      },
      "usage": "Client-side analyzer. Open https://aifinhub.io/hallucination-detector/ and paste a source document + LLM output. Every numeric claim is cross-checked against the source in-browser."
    },
    {
      "slug": "kalshi-poly-arb",
      "url": "https://aifinhub.io/engines/kalshi-poly-arb.js",
      "types": "https://aifinhub.io/engines/kalshi-poly-arb.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "yes_ask": {
            "type": "number"
          },
          "no_ask": {
            "type": "number"
          },
          "fees_bps": {
            "type": "number"
          },
          "slippage_bps": {
            "type": "number"
          },
          "capital_usd": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "yes_ask",
          "no_ask",
          "fees_bps",
          "slippage_bps",
          "capital_usd"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "candidates": {
            "type": "array",
            "items": {
              "type": "object",
              "properties": {
                "subject": {
                  "type": "string"
                },
                "kalshi_ticker": {
                  "type": "string"
                },
                "polymarket_id": {
                  "type": "string"
                },
                "edge_bps": {
                  "type": "number"
                },
                "resolution_risk_flags": {
                  "type": "array",
                  "items": {
                    "type": "string"
                  }
                }
              }
            }
          },
          "generated_at": {
            "type": "string"
          }
        }
      },
      "example": {
        "tool": "kalshi-poly-arb",
        "yes_ask": 0,
        "no_ask": 0,
        "fees_bps": 100,
        "slippage_bps": 50,
        "capital_usd": 1000
      },
      "usage": "Static-data scanner. Open https://aifinhub.io/kalshi-poly-arb/ to browse daily-refreshed arb candidates across Kalshi + Polymarket. Data source: public markets APIs (daily refresh)."
    },
    {
      "slug": "kelly-sizer",
      "url": "https://aifinhub.io/engines/kelly-sizer.js",
      "types": "https://aifinhub.io/engines/kelly-sizer.d.ts",
      "exports": [
        "compute"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "win_rate": {
            "type": "number"
          },
          "win_loss_ratio": {
            "type": "number"
          },
          "max_cap_pct": {
            "type": "number"
          },
          "trades": {
            "type": "number"
          },
          "sims": {
            "type": "number"
          },
          "ruin_threshold_pct": {
            "type": "number"
          },
          "seed": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "win_rate",
          "win_loss_ratio",
          "max_cap_pct",
          "trades",
          "sims",
          "ruin_threshold_pct",
          "seed"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "full_kelly_fraction": {
            "type": "number"
          },
          "recommended_fraction": {
            "type": "number"
          },
          "recommended_bet_size": {
            "type": "number"
          },
          "expected_growth_rate": {
            "type": "number"
          },
          "monte_carlo": {
            "type": "object",
            "properties": {
              "median_final_bankroll": {
                "type": "number"
              },
              "p05_final_bankroll": {
                "type": "number"
              },
              "p95_final_bankroll": {
                "type": "number"
              },
              "max_drawdown_median": {
                "type": "number"
              },
              "ruin_probability": {
                "type": "number"
              }
            }
          }
        }
      },
      "example": {
        "tool": "kelly-sizer",
        "win_rate": 0.55,
        "win_loss_ratio": 1.2,
        "max_cap_pct": 0.05,
        "trades": 250,
        "sims": 1000,
        "ruin_threshold_pct": 0.5,
        "seed": 42
      },
      "usage": "Client-side calculator. Open https://aifinhub.io/kelly-sizer/ and fill in the inputs; results render in-browser."
    },
    {
      "slug": "llm-finance-error-taxonomy",
      "url": "https://aifinhub.io/engines/llm-finance-error-taxonomy.js",
      "types": "https://aifinhub.io/engines/llm-finance-error-taxonomy.d.ts",
      "exports": [
        "compute"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "text": {
            "type": "string"
          },
          "ground_truth": {
            "type": "string"
          }
        },
        "required": [
          "tool",
          "text"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "flagged_modes_count": {
            "type": "integer"
          },
          "flags": {
            "type": "array"
          }
        }
      },
      "example": {
        "tool": "llm_finance_error_taxonomy",
        "text": "XYZW shares trade at €120 with P/E = price * earnings.",
        "ground_truth": ""
      },
      "usage": "Client-side calculator. Open https://aifinhub.io/llm-finance-error-taxonomy/ and fill in the inputs; results render in-browser."
    },
    {
      "slug": "model-selector-finance",
      "url": "https://aifinhub.io/engines/model-selector-finance.js",
      "types": "https://aifinhub.io/engines/model-selector-finance.d.ts",
      "exports": [
        "compute"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "task": {
            "type": "string"
          },
          "latency": {
            "type": "string"
          },
          "cost": {
            "type": "string"
          },
          "context": {
            "type": "string"
          },
          "quality": {
            "type": "string"
          }
        },
        "required": [
          "tool",
          "task",
          "latency",
          "cost",
          "context",
          "quality"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "ranked": {
            "type": "array",
            "items": {
              "type": "object",
              "properties": {
                "model": {
                  "type": "object"
                },
                "score": {
                  "type": "number"
                },
                "rationale": {
                  "type": "string"
                },
                "whyNot": {
                  "type": "string"
                },
                "axes": {
                  "type": "array",
                  "items": {
                    "type": "object",
                    "properties": {
                      "axis": {
                        "type": "string"
                      },
                      "note": {
                        "type": "string"
                      },
                      "passed": {
                        "type": "boolean"
                      }
                    }
                  }
                },
                "monthlyBudgetEstimate": {
                  "type": "number"
                },
                "disqualified": {
                  "type": "boolean"
                }
              }
            }
          }
        }
      },
      "example": {
        "tool": "model_selector_finance",
        "task": "extract",
        "latency": "sub_5s",
        "cost": "b50",
        "context": "k32_200k",
        "quality": "medium"
      },
      "usage": "Client-side calculator. Open https://aifinhub.io/model-selector-finance/ and fill in the inputs; results render in-browser. Also importable as ES module from https://aifinhub.io/engines/model-selector-finance.js — call compute(input) with the JSON shape below."
    },
    {
      "slug": "options-greeks-explorer",
      "url": "https://aifinhub.io/engines/options-greeks-explorer.js",
      "types": "https://aifinhub.io/engines/options-greeks-explorer.d.ts",
      "exports": [
        "compute"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "spot": {
            "type": "number"
          },
          "strike": {
            "type": "number"
          },
          "vol_pct": {
            "type": "number"
          },
          "days_to_exp": {
            "type": "number"
          },
          "rf_pct": {
            "type": "number"
          },
          "div_pct": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "spot",
          "strike",
          "vol_pct",
          "days_to_exp",
          "rf_pct",
          "div_pct"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "price": {
            "type": "number"
          },
          "delta": {
            "type": "number"
          },
          "gamma": {
            "type": "number"
          },
          "theta_per_day": {
            "type": "number"
          },
          "vega_per_1pct": {
            "type": "number"
          },
          "rho_per_1pct": {
            "type": "number"
          }
        }
      },
      "example": {
        "tool": "options-greeks-explorer",
        "spot": 100,
        "strike": 105,
        "vol_pct": 25,
        "days_to_exp": 30,
        "rf_pct": 4.5,
        "div_pct": 0
      },
      "usage": "Client-side pricer. Open https://aifinhub.io/options-greeks-explorer/ and drag inputs to see delta/gamma/theta/vega/rho + payoff curve update live."
    },
    {
      "slug": "options-payoff-builder",
      "url": "https://aifinhub.io/engines/options-payoff-builder.js",
      "types": "https://aifinhub.io/engines/options-payoff-builder.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "side": {
            "type": "string"
          },
          "type": {
            "type": "string"
          },
          "strike": {
            "type": "number"
          },
          "contracts": {
            "type": "number"
          },
          "spot": {
            "type": "number"
          },
          "annual_vol": {
            "type": "number"
          },
          "days_to_expiry": {
            "type": "number"
          },
          "risk_free_rate": {
            "type": "number"
          },
          "dividend_yield": {
            "type": "number"
          },
          "grid_points": {
            "type": "number"
          },
          "spot_range_pct": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "side",
          "type",
          "strike",
          "contracts",
          "spot",
          "annual_vol",
          "days_to_expiry",
          "risk_free_rate",
          "dividend_yield",
          "grid_points",
          "spot_range_pct"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "net_premium": {
            "type": "number"
          },
          "max_profit": {
            "type": "number"
          },
          "max_loss": {
            "type": "number"
          },
          "break_evens": {
            "type": "array",
            "items": {
              "type": "number"
            }
          },
          "aggregated_greeks": {
            "type": "object",
            "properties": {
              "delta": {
                "type": "number"
              },
              "gamma": {
                "type": "number"
              },
              "theta_per_day": {
                "type": "number"
              },
              "vega_per_1pct": {
                "type": "number"
              },
              "rho_per_1pct": {
                "type": "number"
              }
            }
          }
        }
      },
      "example": {
        "tool": "options-payoff-builder",
        "side": "",
        "type": "",
        "strike": 0,
        "contracts": 0,
        "spot": 100,
        "annual_vol": 0.25,
        "days_to_expiry": 30,
        "risk_free_rate": 0.045,
        "dividend_yield": 0,
        "grid_points": 121,
        "spot_range_pct": 0.4,
        "legs": [
          {
            "side": "long",
            "type": "call",
            "strike": 105,
            "contracts": 1
          },
          {
            "side": "short",
            "type": "call",
            "strike": 115,
            "contracts": 1
          }
        ]
      },
      "usage": "Client-side builder. Open https://aifinhub.io/options-payoff-builder/, configure 1–4 legs, see payoff diagram + break-evens + aggregated Greeks."
    },
    {
      "slug": "order-book-replay",
      "url": "https://aifinhub.io/engines/order-book-replay.js",
      "types": "https://aifinhub.io/engines/order-book-replay.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "price": {
            "type": "number"
          },
          "size": {
            "type": "number"
          },
          "depth_bps": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "price",
          "size",
          "depth_bps"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "animation_ready": {
            "type": "boolean"
          },
          "detected_event_types": {
            "type": "array",
            "items": {
              "type": "string"
            }
          },
          "tick_count": {
            "type": "integer"
          },
          "duration_seconds": {
            "type": "number"
          }
        }
      },
      "example": {
        "tool": "order-book-replay",
        "price": 0,
        "size": 0,
        "depth_bps": 10,
        "snapshots": [
          {
            "t": 0,
            "bids": [
              {
                "price": 100.01,
                "size": 200
              },
              {
                "price": 100,
                "size": 350
              },
              {
                "price": 99.99,
                "size": 500
              },
              {
                "price": 99.98,
                "size": 650
              },
              {
                "price": 99.97,
                "size": 800
              }
            ],
            "asks": [
              {
                "price": 100.03,
                "size": 180
              },
              {
                "price": 100.04,
                "size": 320
              },
              {
                "price": 100.05,
                "size": 460
              },
              {
                "price": 100.06,
                "size": 600
              },
              {
                "price": 100.07,
                "size": 740
              }
            ]
          },
          {
            "t": 500,
            "bids": [
              {
                "price": 100.01,
                "size": 250
              },
              {
                "price": 100,
                "size": 400
              },
              {
                "price": 99.99,
                "size": 550
              },
              {
                "price": 99.98,
                "size": 700
              },
              {
                "price": 99.97,
                "size": 850
              }
            ],
            "asks": [
              {
                "price": 100.03,
                "size": 220
              },
              {
                "price": 100.04,
                "size": 360
              },
              {
                "price": 100.05,
                "size": 500
              },
              {
                "price": 100.06,
                "size": 640
              },
              {
                "price": 100.07,
                "size": 780
              }
            ]
          },
          {
            "t": 1000,
            "bids": [
              {
                "price": 100.03,
                "size": 300
              },
              {
                "price": 100.02,
                "size": 450
              },
              {
                "price": 100.01,
                "size": 600
              },
              {
                "price": 100,
                "size": 750
              },
              {
                "price": 99.99,
                "size": 900
              }
            ],
            "asks": [
              {
                "price": 100.05,
                "size": 260
              },
              {
                "price": 100.06,
                "size": 400
              },
              {
                "price": 100.07,
                "size": 540
              },
              {
                "price": 100.08,
                "size": 680
              },
              {
                "price": 100.09,
                "size": 820
              }
            ]
          },
          {
            "t": 1500,
            "bids": [
              {
                "price": 100.03,
                "size": 200
              },
              {
                "price": 100.02,
                "size": 350
              },
              {
                "price": 100.01,
                "size": 500
              },
              {
                "price": 100,
                "size": 650
              },
              {
                "price": 99.99,
                "size": 800
              }
            ],
            "asks": [
              {
                "price": 100.05,
                "size": 300
              },
              {
                "price": 100.06,
                "size": 440
              },
              {
                "price": 100.07,
                "size": 580
              },
              {
                "price": 100.08,
                "size": 720
              },
              {
                "price": 100.09,
                "size": 860
              }
            ]
          },
          {
            "t": 2000,
            "bids": [
              {
                "price": 100.03,
                "size": 250
              },
              {
                "price": 100.02,
                "size": 400
              },
              {
                "price": 100.01,
                "size": 550
              },
              {
                "price": 100,
                "size": 700
              },
              {
                "price": 99.99,
                "size": 850
              }
            ],
            "asks": [
              {
                "price": 100.05,
                "size": 180
              },
              {
                "price": 100.06,
                "size": 320
              },
              {
                "price": 100.07,
                "size": 460
              },
              {
                "price": 100.08,
                "size": 600
              },
              {
                "price": 100.09,
                "size": 740
              }
            ]
          },
          {
            "t": 2500,
            "bids": [
              {
                "price": 100.04,
                "size": 300
              },
              {
                "price": 100.03,
                "size": 450
              },
              {
                "price": 100.02,
                "size": 600
              },
              {
                "price": 100.01,
                "size": 750
              },
              {
                "price": 100,
                "size": 900
              }
            ],
            "asks": [
              {
                "price": 100.06,
                "size": 220
              },
              {
                "price": 100.07,
                "size": 360
              },
              {
                "price": 100.08,
                "size": 500
              },
              {
                "price": 100.09,
                "size": 640
              },
              {
                "price": 100.1,
                "size": 780
              }
            ]
          },
          {
            "t": 3000,
            "bids": [
              {
                "price": 100.05,
                "size": 200
              },
              {
                "price": 100.04,
                "size": 350
              },
              {
                "price": 100.03,
                "size": 500
              },
              {
                "price": 100.02,
                "size": 650
              },
              {
                "price": 100.01,
                "size": 800
              }
            ],
            "asks": [
              {
                "price": 100.07,
                "size": 260
              },
              {
                "price": 100.08,
                "size": 400
              },
              {
                "price": 100.09,
                "size": 540
              },
              {
                "price": 100.1,
                "size": 680
              },
              {
                "price": 100.11,
                "size": 820
              }
            ]
          },
          {
            "t": 3500,
            "bids": [
              {
                "price": 100.06,
                "size": 250
              },
              {
                "price": 100.05,
                "size": 400
              },
              {
                "price": 100.04,
                "size": 550
              },
              {
                "price": 100.03,
                "size": 700
              },
              {
                "price": 100.02,
                "size": 850
              }
            ],
            "asks": [
              {
                "price": 100.08,
                "size": 300
              },
              {
                "price": 100.09,
                "size": 440
              },
              {
                "price": 100.1,
                "size": 580
              },
              {
                "price": 100.11,
                "size": 720
              },
              {
                "price": 100.12,
                "size": 860
              }
            ]
          },
          {
            "t": 4000,
            "bids": [
              {
                "price": 100.05,
                "size": 300
              },
              {
                "price": 100.04,
                "size": 450
              },
              {
                "price": 100.03,
                "size": 600
              },
              {
                "price": 100.02,
                "size": 750
              },
              {
                "price": 100.01,
                "size": 900
              }
            ],
            "asks": [
              {
                "price": 100.07,
                "size": 180
              },
              {
                "price": 100.08,
                "size": 320
              },
              {
                "price": 100.09,
                "size": 460
              },
              {
                "price": 100.1,
                "size": 600
              },
              {
                "price": 100.11,
                "size": 740
              }
            ]
          },
          {
            "t": 4500,
            "bids": [
              {
                "price": 100.06,
                "size": 200
              },
              {
                "price": 100.05,
                "size": 350
              },
              {
                "price": 100.04,
                "size": 500
              },
              {
                "price": 100.03,
                "size": 650
              },
              {
                "price": 100.02,
                "size": 800
              }
            ],
            "asks": [
              {
                "price": 100.08,
                "size": 220
              },
              {
                "price": 100.09,
                "size": 360
              },
              {
                "price": 100.1,
                "size": 500
              },
              {
                "price": 100.11,
                "size": 640
              },
              {
                "price": 100.12,
                "size": 780
              }
            ]
          },
          {
            "t": 5000,
            "bids": [
              {
                "price": 100.06,
                "size": 250
              },
              {
                "price": 100.05,
                "size": 400
              },
              {
                "price": 100.04,
                "size": 550
              },
              {
                "price": 100.03,
                "size": 700
              },
              {
                "price": 100.02,
                "size": 850
              }
            ],
            "asks": [
              {
                "price": 100.08,
                "size": 260
              },
              {
                "price": 100.09,
                "size": 400
              },
              {
                "price": 100.1,
                "size": 540
              },
              {
                "price": 100.11,
                "size": 680
              },
              {
                "price": 100.12,
                "size": 820
              }
            ]
          },
          {
            "t": 5500,
            "bids": [
              {
                "price": 100.04,
                "size": 300
              },
              {
                "price": 100.03,
                "size": 450
              },
              {
                "price": 100.02,
                "size": 600
              },
              {
                "price": 100.01,
                "size": 750
              },
              {
                "price": 100,
                "size": 900
              }
            ],
            "asks": [
              {
                "price": 100.06,
                "size": 300
              },
              {
                "price": 100.07,
                "size": 440
              },
              {
                "price": 100.08,
                "size": 580
              },
              {
                "price": 100.09,
                "size": 720
              },
              {
                "price": 100.1,
                "size": 860
              }
            ]
          }
        ]
      },
      "usage": "Client-side visualizer. Open https://aifinhub.io/order-book-replay/ and drop a Level-2 CSV. The book reconstructs tick-by-tick in the browser. No upload, no backend."
    },
    {
      "slug": "pair-trading-tester",
      "url": "https://aifinhub.io/engines/pair-trading-tester.js",
      "types": "https://aifinhub.io/engines/pair-trading-tester.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "a": {
            "type": "array",
            "items": {
              "type": "number"
            }
          },
          "b": {
            "type": "array",
            "items": {
              "type": "number"
            }
          },
          "lags": {
            "type": "number"
          },
          "z_window": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "a",
          "b",
          "lags",
          "z_window"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "hedge_ratio_beta": {
            "type": "number"
          },
          "ols_r2": {
            "type": "number"
          },
          "adf_t_stat": {
            "type": "number"
          },
          "adf_p_value_band": {
            "type": "string"
          },
          "is_stationary_5pct": {
            "type": "boolean"
          },
          "ou_half_life_days": {
            "type": "number"
          },
          "entry_events": {
            "type": "integer"
          },
          "exit_events": {
            "type": "integer"
          },
          "verdict": {
            "type": "string"
          }
        }
      },
      "example": {
        "tool": "pair-trading-tester",
        "a": [
          100,
          98.5874,
          97.8259,
          98.015,
          97.6033,
          97.5598,
          97.4391,
          95.4593,
          96.8625,
          97.6213,
          96.884,
          97.9378,
          96.7864,
          96.052,
          96.7539,
          97.0884,
          96.2998,
          96.8609,
          96.4113,
          94.7817,
          94.0908,
          95.2396,
          94.912,
          95.9782,
          94.1185,
          94.1316,
          95.6987,
          94.2103,
          94.2116,
          95.9806,
          95.3522,
          94.9435,
          93.114,
          94.4138,
          93.5007,
          92.7732,
          93.5529,
          92.4435,
          91.7068,
          91.0294,
          89.8526,
          90.4241,
          89.7977,
          88.3319,
          90.5591,
          91.0151,
          90.6968,
          90.7679,
          89.7283,
          90.0064,
          90.209,
          92.9212,
          92.3561,
          91.9658,
          89.6928,
          89.0712,
          89.7689,
          89.4756,
          89.6975,
          89.6835,
          89.6376,
          90.0946,
          90.1572,
          90.8464,
          93.7497,
          92.1072,
          93.1928,
          94.5939,
          91.9662,
          94.5231,
          95.2861,
          95.7917,
          95.5093,
          94.1203,
          93.5651,
          92.9154,
          94.495,
          94.4734,
          94.3377,
          95.4258
        ],
        "b": [
          151.141,
          149.3602,
          148.5811,
          149.3006,
          149.0083,
          149.3586,
          148.3213,
          145.2459,
          146.8073,
          148.1455,
          147.1322,
          148.4226,
          147.5568,
          146.0558,
          145.4098,
          146.5035,
          146.4691,
          147.5213,
          145.983,
          144.2597,
          142.6992,
          144.0918,
          143.485,
          145.0805,
          142.3363,
          141.9733,
          144.8319,
          143.6638,
          144.3719,
          147.3897,
          146.2313,
          146.8656,
          144.1777,
          145.6877,
          143.6726,
          142.1663,
          144.0035,
          140.4674,
          140.1333,
          139.8269,
          138.2176,
          137.391,
          137.1818,
          134.8946,
          138.3316,
          138.8633,
          138.7863,
          139.4953,
          137.8307,
          138.0143,
          138.1207,
          141.8669,
          140.5081,
          139.9323,
          136.2529,
          135.6546,
          137.3739,
          137.2101,
          138.5398,
          139.4239,
          138.4136,
          138.4121,
          138.646,
          137.7651,
          142.8305,
          140.5458,
          142.8138,
          145.3761,
          141.5616,
          144.592,
          146.166,
          146.9859,
          146.5194,
          144.7299,
          144.0425,
          142.9379,
          144.9803,
          145.411,
          144.2937,
          146.1881
        ],
        "lags": 1,
        "z_window": 30
      },
      "usage": "Client-side tester. Open https://aifinhub.io/pair-trading-tester/ and paste a two-asset price CSV. Engle-Granger + ADF + OU half-life + z-score all in-browser."
    },
    {
      "slug": "position-sizing-edge-variance",
      "url": "https://aifinhub.io/engines/position-sizing-edge-variance.js",
      "types": "https://aifinhub.io/engines/position-sizing-edge-variance.d.ts",
      "exports": [
        "compute"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "edge_mean": {
            "type": "number"
          },
          "edge_stddev": {
            "type": "number"
          },
          "outcome_variance": {
            "type": "number"
          },
          "kelly_fraction": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "edge_mean",
          "edge_stddev",
          "outcome_variance",
          "kelly_fraction"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "deterministic_kelly": {
            "type": "number"
          },
          "bayesian_kelly": {
            "type": "number"
          },
          "conservative_kelly": {
            "type": "number"
          },
          "cvar_5": {
            "type": "number"
          }
        }
      },
      "example": {
        "tool": "position-sizing-edge-variance",
        "edge_mean": 0.04,
        "edge_stddev": 0.02,
        "outcome_variance": 0.04,
        "kelly_fraction": 0.25
      },
      "usage": "Client-side calculator. Open https://aifinhub.io/position-sizing-edge-variance/ and fill in the inputs; results render in-browser."
    },
    {
      "slug": "price-blind-auditor",
      "url": "https://aifinhub.io/engines/price-blind-auditor.js",
      "types": "https://aifinhub.io/engines/price-blind-auditor.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "text": {
            "type": "string"
          }
        },
        "required": [
          "tool",
          "text"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "line_count": {
            "type": "integer"
          },
          "leakage_score": {
            "type": "number"
          },
          "verdict": {
            "type": "string"
          },
          "hits": {
            "type": "array",
            "items": {
              "type": "object",
              "properties": {
                "rule_id": {
                  "type": "string"
                },
                "severity": {
                  "type": "string"
                },
                "line": {
                  "type": "integer"
                },
                "match": {
                  "type": "string"
                },
                "why": {
                  "type": "string"
                }
              }
            }
          }
        }
      },
      "example": {
        "tool": "price-blind-auditor",
        "text": ""
      },
      "usage": "Client-side auditor. Open https://aifinhub.io/price-blind-auditor/ and paste a research prompt bundle. Every line is scanned for price/direction/position-state leakage; findings render in-browser."
    },
    {
      "slug": "prompt-injection-tester",
      "url": "https://aifinhub.io/engines/prompt-injection-tester.js",
      "types": "https://aifinhub.io/engines/prompt-injection-tester.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "attack_id": {
            "type": "string"
          },
          "output": {
            "type": "string"
          }
        },
        "required": [
          "tool",
          "attack_id",
          "output"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "total_attacks": {
            "type": "integer"
          },
          "robustness_percent": {
            "type": "number"
          },
          "success_count": {
            "type": "integer"
          },
          "partial_count": {
            "type": "integer"
          },
          "refused_count": {
            "type": "integer"
          },
          "results": {
            "type": "array",
            "items": {
              "type": "object",
              "properties": {
                "attack_id": {
                  "type": "string"
                },
                "category": {
                  "type": "string"
                },
                "outcome": {
                  "type": "string",
                  "enum": [
                    "success",
                    "partial",
                    "refused"
                  ]
                },
                "latency_ms": {
                  "type": "integer"
                },
                "output": {
                  "type": "string"
                }
              }
            }
          }
        }
      },
      "example": {
        "tool": "prompt-injection-tester",
        "attack_id": "",
        "output": ""
      },
      "usage": "BYO-key playground. Open https://aifinhub.io/prompt-injection-tester/, pick provider + model, paste target system prompt + API key. Runs 24 documented injection attacks client-side and classifies each outcome."
    },
    {
      "slug": "prompt-regression-tester",
      "url": "https://aifinhub.io/engines/prompt-regression-tester.js",
      "types": "https://aifinhub.io/engines/prompt-regression-tester.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "baseline": {
            "type": "string"
          },
          "label": {
            "type": "string"
          },
          "output": {
            "type": "string"
          },
          "n": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "baseline",
          "label",
          "output",
          "n"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "per_model": {
            "type": "array",
            "items": {
              "type": "object",
              "properties": {
                "model": {
                  "type": "string"
                },
                "outputs": {
                  "type": "array",
                  "items": {
                    "type": "string"
                  }
                },
                "drift_score": {
                  "type": "number"
                },
                "mean_length": {
                  "type": "number"
                }
              }
            }
          },
          "pairwise_agreement": {
            "type": "number"
          }
        }
      },
      "example": {
        "tool": "prompt-regression-tester",
        "baseline": "",
        "label": "",
        "output": "",
        "n": 3
      },
      "usage": "Client-side playground. Open https://aifinhub.io/prompt-regression-tester/ to run one prompt across Claude/GPT/Gemini using your own keys. Keys stay in the browser."
    },
    {
      "slug": "quant-interview-question-generator",
      "url": "https://aifinhub.io/engines/quant-interview-question-generator.js",
      "types": "https://aifinhub.io/engines/quant-interview-question-generator.d.ts",
      "exports": [
        "compute"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "difficulty": {
            "type": "string"
          },
          "n": {
            "type": "number"
          },
          "seed": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "difficulty",
          "n",
          "seed"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "questions": {
            "type": "array"
          },
          "count": {
            "type": "integer"
          }
        }
      },
      "example": {
        "tool": "quant-interview-question-generator",
        "difficulty": "medium",
        "n": 5,
        "seed": 7
      },
      "usage": "Client-side calculator. Open https://aifinhub.io/quant-interview-question-generator/ and fill in the inputs; results render in-browser."
    },
    {
      "slug": "returns-distribution-analyzer",
      "url": "https://aifinhub.io/engines/returns-distribution-analyzer.js",
      "types": "https://aifinhub.io/engines/returns-distribution-analyzer.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "bins": {
            "type": "number"
          },
          "returns": {
            "type": "array",
            "items": {
              "type": "number"
            }
          }
        },
        "required": [
          "tool",
          "bins",
          "returns"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "mean": {
            "type": "number"
          },
          "stdev": {
            "type": "number"
          },
          "median": {
            "type": "number"
          },
          "skewness": {
            "type": "number"
          },
          "excess_kurtosis": {
            "type": "number"
          },
          "jarque_bera_stat": {
            "type": "number"
          },
          "jarque_bera_p_value": {
            "type": "number"
          },
          "negative_tail_mass": {
            "type": "number"
          },
          "positive_tail_mass": {
            "type": "number"
          },
          "tail_excess_ratio": {
            "type": "number"
          }
        }
      },
      "example": {
        "tool": "returns-distribution-analyzer",
        "bins": 30,
        "returns": [
          0.01,
          0.02,
          -0.005,
          0.015,
          -0.01
        ]
      },
      "usage": "Client-side analyzer. Open https://aifinhub.io/returns-distribution-analyzer/ and paste a returns CSV. Histogram, normal QQ plot, Jarque-Bera, and 3-sigma tail-mass diagnostics render in-browser."
    },
    {
      "slug": "risk-adjusted-returns",
      "url": "https://aifinhub.io/engines/risk-adjusted-returns.js",
      "types": "https://aifinhub.io/engines/risk-adjusted-returns.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "risk_free_annual": {
            "type": "number"
          },
          "returns": {
            "type": "array",
            "items": {
              "type": "number"
            }
          },
          "benchmark": {
            "type": "array",
            "items": {
              "type": "number"
            }
          }
        },
        "required": [
          "tool",
          "risk_free_annual",
          "returns",
          "benchmark"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "sharpe_ratio": {
            "type": "number"
          },
          "sortino_ratio": {
            "type": "number"
          },
          "calmar_ratio": {
            "type": "number"
          },
          "omega_ratio": {
            "type": "number"
          },
          "max_drawdown": {
            "type": "number"
          },
          "alpha_annual": {
            "type": "number"
          },
          "beta": {
            "type": "number"
          },
          "information_ratio": {
            "type": "number"
          },
          "tracking_error_annual": {
            "type": "number"
          }
        }
      },
      "example": {
        "tool": "risk-adjusted-returns",
        "risk_free_annual": 0,
        "returns": [
          0.01,
          0.02,
          -0.005,
          0.015,
          -0.01
        ],
        "benchmark": [
          0.01,
          0.02,
          -0.005,
          0.015,
          -0.01
        ]
      },
      "usage": "Client-side calculator. Open https://aifinhub.io/risk-adjusted-returns/ and paste a returns CSV. Sharpe/Sortino/Calmar/Omega/alpha/beta/IR are computed in-browser."
    },
    {
      "slug": "sec-filing-chunk-optimizer",
      "url": "https://aifinhub.io/engines/sec-filing-chunk-optimizer.js",
      "types": "https://aifinhub.io/engines/sec-filing-chunk-optimizer.d.ts",
      "exports": [
        "compute"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "archetype_id": {
            "type": "string"
          },
          "chunk_size": {
            "type": "number"
          },
          "overlap_pct": {
            "type": "number"
          },
          "strategy": {
            "type": "string"
          },
          "embedding_model_id": {
            "type": "string"
          },
          "query_reembed_count": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "archetype_id",
          "chunk_size",
          "overlap_pct",
          "strategy",
          "embedding_model_id",
          "query_reembed_count"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "archetype": {
            "type": "object",
            "properties": {
              "id": {
                "type": "string"
              },
              "name": {
                "type": "string"
              },
              "approxTokens": {
                "type": "integer"
              }
            }
          },
          "embedding": {
            "type": "object",
            "properties": {
              "id": {
                "type": "string"
              },
              "name": {
                "type": "string"
              },
              "usdPerMToken": {
                "type": "number"
              }
            }
          },
          "strategy": {
            "type": "string",
            "enum": [
              "structural",
              "recursive",
              "semantic"
            ]
          },
          "chunkCount": {
            "type": "integer"
          },
          "avgTokens": {
            "type": "number"
          },
          "minTokens": {
            "type": "integer"
          },
          "maxTokens": {
            "type": "integer"
          },
          "tokensIngested": {
            "type": "integer"
          },
          "embeddingCostOnce": {
            "type": "number"
          },
          "embeddingCostPer100Queries": {
            "type": "number"
          },
          "warnings": {
            "type": "array",
            "items": {
              "type": "string"
            }
          },
          "strategyNotes": {
            "type": "string"
          }
        }
      },
      "example": {
        "tool": "sec_filing_chunk_optimizer",
        "archetype_id": "10k-body",
        "chunk_size": 1024,
        "overlap_pct": 0.1,
        "strategy": "structural",
        "embedding_model_id": "openai-embed-3-small",
        "query_reembed_count": 100
      },
      "usage": "Client-side calculator. Open https://aifinhub.io/sec-filing-chunk-optimizer/ and fill in the inputs; results render in-browser. Also importable as ES module from https://aifinhub.io/engines/sec-filing-chunk-optimizer.js — call compute(input) with the JSON shape below."
    },
    {
      "slug": "sharpe-vs-sortino-calculator",
      "url": "https://aifinhub.io/engines/sharpe-vs-sortino-calculator.js",
      "types": "https://aifinhub.io/engines/sharpe-vs-sortino-calculator.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "rf_annual": {
            "type": "number"
          },
          "returns": {
            "type": "array",
            "items": {
              "type": "number"
            }
          }
        },
        "required": [
          "tool",
          "rf_annual",
          "returns"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "sharpe": {
            "type": "number"
          },
          "sortino": {
            "type": "number"
          },
          "calmar": {
            "type": "number"
          },
          "omega": {
            "type": "number"
          },
          "max_drawdown": {
            "type": "number"
          }
        }
      },
      "example": {
        "tool": "sharpe-vs-sortino-calculator",
        "rf_annual": 0.04,
        "returns": [
          0.01,
          0.02,
          -0.005,
          0.015,
          -0.01
        ]
      },
      "usage": "Client-side calculator. Open https://aifinhub.io/sharpe-vs-sortino-calculator/ and fill in the inputs; results render in-browser."
    },
    {
      "slug": "statistical-arbitrage-capacity",
      "url": "https://aifinhub.io/engines/statistical-arbitrage-capacity.js",
      "types": "https://aifinhub.io/engines/statistical-arbitrage-capacity.d.ts",
      "exports": [
        "compute"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "signal_half_life_days": {
            "type": "number"
          },
          "daily_volume_usd": {
            "type": "number"
          },
          "slippage_bps": {
            "type": "number"
          },
          "fee_bps": {
            "type": "number"
          },
          "target_sharpe": {
            "type": "number"
          },
          "alpha_per_trade_bps": {
            "type": "number"
          },
          "impact_k": {
            "type": "number"
          },
          "trading_days": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "signal_half_life_days",
          "daily_volume_usd",
          "slippage_bps",
          "fee_bps",
          "target_sharpe",
          "alpha_per_trade_bps",
          "impact_k",
          "trading_days"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "max_aum": {
            "type": "number"
          },
          "practical_aum": {
            "type": "number"
          },
          "trades_per_year": {
            "type": "number"
          },
          "capacity_curve": {
            "type": "array"
          }
        }
      },
      "example": {
        "tool": "statistical-arbitrage-capacity",
        "signal_half_life_days": 5,
        "daily_volume_usd": 50000000,
        "slippage_bps": 3,
        "fee_bps": 1,
        "target_sharpe": 2,
        "alpha_per_trade_bps": 12,
        "impact_k": 0.2,
        "trading_days": 252
      },
      "usage": "Client-side calculator. Open https://aifinhub.io/statistical-arbitrage-capacity/ and fill in the inputs; results render in-browser."
    },
    {
      "slug": "structured-schema-validator-finance",
      "url": "https://aifinhub.io/engines/structured-schema-validator-finance.js",
      "types": "https://aifinhub.io/engines/structured-schema-validator-finance.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "schema_id": {
            "type": "string"
          }
        },
        "required": [
          "tool",
          "schema_id"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "pass": {
            "type": "boolean"
          },
          "fields": {
            "type": "array",
            "items": {
              "type": "object",
              "properties": {
                "field": {
                  "type": "string"
                },
                "status": {
                  "type": "string",
                  "enum": [
                    "ok",
                    "missing",
                    "type_mismatch",
                    "enum_mismatch",
                    "out_of_range",
                    "too_short"
                  ]
                },
                "message": {
                  "type": "string"
                }
              }
            }
          },
          "sanityFlags": {
            "type": "array",
            "items": {
              "type": "string"
            }
          },
          "parseError": {
            "type": "string"
          }
        }
      },
      "example": {
        "tool": "structured_schema_validator_finance",
        "schema_id": "trade_decision",
        "json": {
          "ticker": "AAPL",
          "side": "long",
          "size_shares": 250,
          "rationale": "Earnings beat confirmed the margin-expansion thesis; sized for 1% portfolio risk against the declared stop.",
          "stop_loss": 178.5,
          "take_profit": 212
        }
      },
      "usage": "Client-side calculator. Open https://aifinhub.io/structured-schema-validator-finance/ and fill in the inputs; results render in-browser. Also importable as ES module from https://aifinhub.io/engines/structured-schema-validator-finance.js — call compute(input) with the JSON shape below."
    },
    {
      "slug": "synthetic-market-data-generator",
      "url": "https://aifinhub.io/engines/synthetic-market-data-generator.js",
      "types": "https://aifinhub.io/engines/synthetic-market-data-generator.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "seed": {
            "type": "number"
          },
          "s0": {
            "type": "number"
          },
          "drift": {
            "type": "number"
          },
          "vol": {
            "type": "number"
          },
          "days": {
            "type": "number"
          },
          "trading_days_per_year": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "seed",
          "s0",
          "drift",
          "vol",
          "days",
          "trading_days_per_year"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "model": {
            "type": "string",
            "enum": [
              "gbm",
              "garch",
              "regime",
              "pair"
            ]
          },
          "prices": {
            "type": "array",
            "items": {
              "type": "number"
            },
            "description": "Single-series result (gbm / garch / regime)."
          },
          "stats": {
            "type": "object",
            "properties": {
              "annReturn": {
                "type": "number"
              },
              "annVol": {
                "type": "number"
              },
              "sharpe": {
                "type": "number"
              },
              "maxDrawdown": {
                "type": "number"
              }
            }
          },
          "pricesA": {
            "type": "array",
            "items": {
              "type": "number"
            },
            "description": "Pair result, leg A."
          },
          "pricesB": {
            "type": "array",
            "items": {
              "type": "number"
            },
            "description": "Pair result, leg B."
          },
          "statsA": {
            "type": "object"
          },
          "statsB": {
            "type": "object"
          }
        }
      },
      "example": {
        "tool": "synthetic-market-data-generator",
        "seed": 42,
        "s0": 100,
        "drift": 8,
        "vol": 20,
        "days": 252,
        "trading_days_per_year": 252
      },
      "usage": "Client-side synthetic price series generator. Open https://aifinhub.io/synthetic-market-data-generator/ and select a model (GBM, GARCH(1,1), regime-switching, or Gaussian-copula pairs). Set parameters + optional seed, download CSV or JSON."
    },
    {
      "slug": "token-cost-optimizer",
      "url": "https://aifinhub.io/engines/token-cost-optimizer.js",
      "types": "https://aifinhub.io/engines/token-cost-optimizer.d.ts",
      "exports": [
        "compute"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "input_tokens_per_call": {
            "type": "number"
          },
          "output_tokens_per_call": {
            "type": "number"
          },
          "calls_per_idea": {
            "type": "number"
          },
          "retry_rate": {
            "type": "number"
          },
          "ideas_per_day": {
            "type": "number"
          },
          "validation_rate": {
            "type": "number"
          },
          "cache_hit_rate": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "input_tokens_per_call",
          "output_tokens_per_call",
          "calls_per_idea",
          "retry_rate",
          "ideas_per_day",
          "validation_rate",
          "cache_hit_rate"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "cost_per_idea_usd": {
            "type": "number"
          },
          "monthly_cost_usd": {
            "type": "number"
          },
          "cost_per_validated_trade_usd": {
            "type": "number"
          },
          "optimization_hints": {
            "type": "array",
            "items": {
              "type": "string"
            }
          }
        }
      },
      "example": {
        "tool": "token-cost-optimizer",
        "input_tokens_per_call": 6000,
        "output_tokens_per_call": 1200,
        "calls_per_idea": 4,
        "retry_rate": 0.15,
        "ideas_per_day": 20,
        "validation_rate": 0.2,
        "cache_hit_rate": 0.5
      },
      "usage": "Client-side calculator. Open https://aifinhub.io/token-cost-optimizer/ to estimate cost-per-idea across LLM providers for a trading research loop."
    },
    {
      "slug": "trading-system-blueprinter",
      "url": "https://aifinhub.io/engines/trading-system-blueprinter.js",
      "types": "https://aifinhub.io/engines/trading-system-blueprinter.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "data_source": {
            "type": "string"
          },
          "llm_provider": {
            "type": "string"
          },
          "broker": {
            "type": "string"
          },
          "storage": {
            "type": "string"
          },
          "risk_engine": {
            "type": "string"
          },
          "logger": {
            "type": "string"
          }
        },
        "required": [
          "tool",
          "data_source",
          "llm_provider",
          "broker",
          "storage",
          "risk_engine",
          "logger"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "mermaid_diagram": {
            "type": "string"
          },
          "repo_zip_base64": {
            "type": "string"
          },
          "integrations": {
            "type": "array",
            "items": {
              "type": "string"
            }
          }
        }
      },
      "example": {
        "tool": "trading_system_blueprinter",
        "data_source": "databento",
        "llm_provider": "anthropic",
        "broker": "alpaca",
        "storage": "duckdb",
        "risk_engine": "fractional_kelly",
        "logger": "jsonl_file"
      },
      "usage": "Client-side generator. Open https://aifinhub.io/trading-system-blueprinter/ to pick components and download a Mermaid diagram + starter repo scaffold (ZIP)."
    },
    {
      "slug": "var-backtest-kupiec-christoffersen",
      "url": "https://aifinhub.io/engines/var-backtest-kupiec-christoffersen.js",
      "types": "https://aifinhub.io/engines/var-backtest-kupiec-christoffersen.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "confidence_level": {
            "type": "number"
          },
          "pnl": {
            "type": "array",
            "items": {
              "type": "number"
            }
          },
          "var_series": {
            "type": "array",
            "items": {
              "type": "number"
            }
          }
        },
        "required": [
          "tool",
          "confidence_level",
          "pnl",
          "var_series"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "exceptions": {
            "type": "integer"
          },
          "kupiec_p_value": {
            "type": "number"
          },
          "christoffersen_p_value": {
            "type": "number"
          },
          "joint_p_value": {
            "type": "number"
          }
        }
      },
      "example": {
        "tool": "var-backtest-kupiec-christoffersen",
        "confidence_level": 0.95,
        "pnl": [
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      },
      "usage": "Client-side calculator. Open https://aifinhub.io/var-backtest-kupiec-christoffersen/ and fill in the inputs; results render in-browser."
    },
    {
      "slug": "walk-forward-validation-visualizer",
      "url": "https://aifinhub.io/engines/walk-forward-validation-visualizer.js",
      "types": "https://aifinhub.io/engines/walk-forward-validation-visualizer.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "num_windows": {
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          },
          "train_pct": {
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          }
        },
        "required": [
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          "num_windows",
          "train_pct"
        ]
      },
      "output_schema": {
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        "properties": {
          "mean_is_sharpe": {
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          },
          "mean_oos_sharpe": {
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          },
          "drop_pct": {
            "type": "number"
          },
          "windows": {
            "type": "array"
          }
        }
      },
      "example": {
        "tool": "walk-forward-validation-visualizer",
        "num_windows": 4,
        "train_pct": 0.7,
        "rows": [
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            "strategy": 0.008538,
            "benchmark": 0.010128,
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            "benchmark": -0.006723,
            "date": "2024-11-13"
          },
          {
            "strategy": 0.001341,
            "benchmark": 0.01639,
            "date": "2024-11-14"
          },
          {
            "strategy": -0.008409,
            "benchmark": -0.004769,
            "date": "2024-11-16"
          },
          {
            "strategy": 0.009245,
            "benchmark": 0.003726,
            "date": "2024-11-17"
          },
          {
            "strategy": -0.002429,
            "benchmark": -0.00393,
            "date": "2024-11-19"
          },
          {
            "strategy": 0.002911,
            "benchmark": 0.003127,
            "date": "2024-11-20"
          },
          {
            "strategy": 0.026725,
            "benchmark": -0.01297,
            "date": "2024-11-21"
          },
          {
            "strategy": 0.006205,
            "benchmark": 0.000173,
            "date": "2024-11-23"
          },
          {
            "strategy": -0.011584,
            "benchmark": 0.008726,
            "date": "2024-11-24"
          },
          {
            "strategy": 0.006461,
            "benchmark": -0.005389,
            "date": "2024-11-26"
          },
          {
            "strategy": 0.023686,
            "benchmark": -0.001837,
            "date": "2024-11-27"
          },
          {
            "strategy": -0.013444,
            "benchmark": -0.001276,
            "date": "2024-11-28"
          },
          {
            "strategy": 0.015965,
            "benchmark": 0.011464,
            "date": "2024-11-30"
          },
          {
            "strategy": 0.025414,
            "benchmark": -0.002788,
            "date": "2024-12-01"
          },
          {
            "strategy": 0.016531,
            "benchmark": 0.012993,
            "date": "2024-12-03"
          },
          {
            "strategy": 0.009368,
            "benchmark": 0.001694,
            "date": "2024-12-04"
          },
          {
            "strategy": -0.01292,
            "benchmark": 0.00199,
            "date": "2024-12-05"
          },
          {
            "strategy": 0.005555,
            "benchmark": 0.005871,
            "date": "2024-12-07"
          },
          {
            "strategy": 0.002591,
            "benchmark": 0.002151,
            "date": "2024-12-08"
          },
          {
            "strategy": 0.001749,
            "benchmark": -0.009941,
            "date": "2024-12-10"
          },
          {
            "strategy": -0.001953,
            "benchmark": 0.004667,
            "date": "2024-12-11"
          },
          {
            "strategy": 0.003645,
            "benchmark": 0.011478,
            "date": "2024-12-12"
          },
          {
            "strategy": -0.004807,
            "benchmark": 0.010766,
            "date": "2024-12-14"
          },
          {
            "strategy": 0.008585,
            "benchmark": 0.001628,
            "date": "2024-12-15"
          },
          {
            "strategy": 0.00677,
            "benchmark": 0.007118,
            "date": "2024-12-17"
          },
          {
            "strategy": -0.019627,
            "benchmark": 0.002115,
            "date": "2024-12-18"
          }
        ],
        "mode": "rolling"
      },
      "usage": "Client-side calculator. Open https://aifinhub.io/walk-forward-validation-visualizer/ and fill in the inputs; results render in-browser."
    },
    {
      "slug": "walk-forward-validator",
      "url": "https://aifinhub.io/engines/walk-forward-validator.js",
      "types": "https://aifinhub.io/engines/walk-forward-validator.d.ts",
      "exports": [
        "compute",
        "computeBody"
      ],
      "input_schema": {
        "type": "object",
        "properties": {
          "tool": {
            "type": "string"
          },
          "returns": {
            "type": "array",
            "items": {
              "type": "number"
            }
          },
          "is_len": {
            "type": "number"
          },
          "oos_len": {
            "type": "number"
          },
          "step": {
            "type": "number"
          }
        },
        "required": [
          "tool",
          "returns",
          "is_len",
          "oos_len",
          "step"
        ]
      },
      "output_schema": {
        "type": "object",
        "properties": {
          "windows": {
            "type": "array",
            "items": {
              "type": "object",
              "properties": {
                "start_date": {
                  "type": "string"
                },
                "end_date": {
                  "type": "string"
                },
                "is_sharpe": {
                  "type": "number"
                },
                "oos_sharpe": {
                  "type": "number"
                }
              }
            }
          },
          "walk_forward_efficiency": {
            "type": "number"
          },
          "concatenated_oos_sharpe": {
            "type": "number"
          }
        }
      },
      "example": {
        "tool": "walk-forward-validator",
        "returns": [
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          0.002904,
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          0.007983,
          0.000161,
          0.021717,
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          0.004743,
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          0.001381,
          0.001706,
          0.010257,
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          0.011349,
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          0.018344,
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          -0.008494,
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          0.010621,
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          0.000113,
          0.011247,
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          0.000106,
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          0.008483,
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          0.0007,
          -0.002969,
          -0.007622,
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          -0.005261,
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          0.009383,
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          -0.001566,
          -0.019978,
          0.001681,
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          -0.00071,
          0.023267,
          0.010219,
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        ],
        "is_len": 252,
        "oos_len": 63,
        "step": 63,
        "mode": "rolling"
      },
      "usage": "Client-side validator. Open https://aifinhub.io/walk-forward-validator/ and paste a returns CSV. Rolling/expanding IS+OOS windows, per-window Sharpe, concatenated OOS equity."
    }
  ]
}