{ "version": "1.0", "format": "es-module-import", "generated_at": "2026-05-10T21:48:54.402Z", "base": "https://aifinhub.io/engines/", "hub": "aifinhub", "total": 45, "usage": "Import https://aifinhub.io/engines/{slug}.js as an ES module and call compute(input). All engines are tree-shaken self-contained ES2020+, no external imports, safe in browser / Node / Deno. The compute() return shape matches the legacy /api/{slug}/ JSON response.", "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": { "type": "string" }, "input_tokens_per_step": { "type": "number" }, "output_tokens_per_step": { "type": "number" }, "steps_per_loop": { "type": "number" }, "convergence_check_pct": { "type": "number" }, "markets_per_day": { "type": "number" }, "target_monthly_usd": { "type": "number" }, "calendar_mode": { "type": "string" } }, "required": [ "tool", "model_id", "input_tokens_per_step", "output_tokens_per_step", "steps_per_loop", "convergence_check_pct", "markets_per_day", "target_monthly_usd", "calendar_mode" ] }, "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" } } }, "steps": { "type": "array", "items": { "type": "object", "properties": { "label": { "type": "string" }, "kind": { "type": "string", "enum": [ "step", "convergence" ] }, "inputCost": { "type": "number" }, "outputCost": { "type": "number" }, "totalCost": { "type": "number" } } } }, "costPerLoop": { "type": "number" }, "toolUseSubtotal": { "type": "number" }, "convergenceCost": { "type": "number" }, "costPerDay": { "type": "number" }, "costPerMonth": { "type": "number" }, "daysPerMonth": { "type": "integer" }, "tokensPerLoop": { "type": "number" }, "blendedUsdPer1KTokens": { "type": "number" }, "withinBudget": { "type": "boolean" }, "budgetUtilization": { "type": "number" } } }, "example": { "tool": "agent_cost_envelope_calculator", "model_id": "claude-sonnet-4-5", "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" }, "skill_md": { "type": "string" }, "sample_input_text": { "type": "string" }, "model": { "type": "string" }, "max_output_tokens": { "type": "integer" }, "anthropic_api_key": { "type": "string" } }, "required": [ "tool", "skill_md", "sample_input_text", "model", "max_output_tokens", "anthropic_api_key" ] }, "output_schema": { "type": "object", "properties": { "structured_output": { "type": "object" }, "latency_ms": { "type": "number" }, "input_tokens": { "type": "integer" }, "output_tokens": { "type": "integer" }, "cost_usd": { "type": "number" } } }, "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-..." }, "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" ], "input_schema": { "type": "object", "properties": { "tool": { "type": "string" }, "s": { "type": "number" }, "max_combos": { "type": "number" }, "seed": { "type": "number" } }, "required": [ "tool", "s", "max_combos", "seed" ] }, "output_schema": { "type": "object", "properties": { "probability_of_backtest_overfitting": { "type": "number" }, "deflated_sharpe_ratio": { "type": "number" }, "expected_max_sharpe_null": { "type": "number" }, "rank_consistency": { "type": "number" }, "verdict": { "type": "string" } } }, "example": { "tool": "backtest-overfitting-score", "s": 8, "max_combos": 500, "seed": 42 }, "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 ] }, "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, "steps": 60 }, "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 }, "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": 0.28, "days_to_expiry": 45, "risk_free_rate": 0.045, "dividend_yield": 0.015, "grid_points": 121, "spot_range_pct": 0.4 }, "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 }, "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": [ 0.01, 0.02, -0.005, 0.015, -0.01 ], "b": [ 0.01, 0.02, -0.005, 0.015, -0.01 ], "lags": 1, "z_window": 60 }, "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": "" }, "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": [ 0.01, 0.02, -0.005, 0.015, -0.01 ], "var_series": [ 0.01, 0.02, -0.005, 0.015, -0.01 ] }, "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": { "type": "number" }, "train_pct": { "type": "number" } }, "required": [ "tool", "num_windows", "train_pct" ] }, "output_schema": { "type": "object", "properties": { "mean_is_sharpe": { "type": "number" }, "mean_oos_sharpe": { "type": "number" }, "drop_pct": { "type": "number" }, "windows": { "type": "array" } } }, "example": { "tool": "walk-forward-validation-visualizer", "num_windows": 8, "train_pct": 0.7 }, "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": [ 0.01, 0.02, -0.005, 0.015, -0.01 ], "is_len": 252, "oos_len": 63, "step": 63 }, "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." } ] }