> ## Documentation Index > Fetch the complete documentation index at: https://rekko.ai/docs/llms.txt > Use this file to discover all available pages before exploring further. # Generate Signal > Generate an actionable strategy signal for a market. Default: returns 202 with analysis_id for polling. With ?wait=true: blocks until pipeline completes (30-90 seconds). If a cached analysis exists (<24h): returns immediately. Use "force": true to bypass cache. ## OpenAPI ````yaml POST /v1/signals openapi: 3.1.0 info: title: Rekko AI — Prediction Market Intelligence description: >- The brain for prediction market trading. Deep AI research, Bayesian causal decomposition, portfolio-aware strategy signals, cross-platform arbitrage, and execution guidance — all in one API. Covers Kalshi, Polymarket, Robinhood, and Coinbase. Clean flat JSON designed for developers and autonomous trading agents. contact: name: Rekko AI url: https://rekko.ai/ license: name: Proprietary version: 1.0.0 servers: - url: https://api.rekko.ai security: [] tags: - name: Markets description: Prediction market listings, history, resolution, and execution guidance - name: Insights description: AI-powered research insights with causal decomposition - name: Strategy description: >- Actionable trading signals with Kelly-derived position sizing and causal decomposition - name: Portfolio description: Portfolio-aware strategy, correlation analysis, and hedge recommendations - name: Arbitrage description: Cross-platform arbitrage detection (Kalshi vs Polymarket vs Robinhood) - name: Analytics description: Calibration metrics, sentiment, and performance tracking - name: Streaming description: Real-time SSE event stream and webhooks - name: Consensus description: Agent trade aggregation and crowd probability paths: /v1/signals: post: tags: - Strategy summary: Generate AI strategy signal description: |- Generate an actionable strategy signal for a market. Default: returns 202 with analysis_id for polling. With ?wait=true: blocks until pipeline completes (30-90 seconds). If a cached analysis exists (<24h): returns immediately. Use "force": true to bypass cache. operationId: /v1/signals parameters: - name: wait in: query required: false schema: type: boolean description: Block until analysis completes (up to 5 min) default: false title: Wait description: Block until analysis completes (up to 5 min) - name: expand in: query required: false schema: type: string description: Comma-separated expansions default: '' title: Expand description: Comma-separated expansions requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/SignalRequest' responses: '200': description: Successful Response content: application/json: schema: $ref: '#/components/schemas/Signal' '422': description: Validation Error content: application/json: schema: $ref: '#/components/schemas/HTTPValidationError' components: schemas: SignalRequest: properties: platform: type: string title: Platform description: 'Filter by platform: ''kalshi'', ''polymarket'', or ''robinhood''' default: '' market_id: type: string title: Market Id description: Platform-specific market identifier default: '' market_query: type: string title: Market Query description: Free-text market question (used if market_id not provided) default: '' force: type: boolean title: Force description: Force fresh analysis even if a cached result exists default: false type: object title: SignalRequest description: Request body for the signal endpoint. example: force: false market_id: KXFED-26MAR19 market_query: '' platform: kalshi Signal: properties: platform: type: string title: Platform description: kalshi, polymarket, robinhood, or coinbase market_id: type: string title: Market Id description: Platform-specific market identifier title: type: string title: Title description: Market question recommendation: type: string enum: - BUY_YES - BUY_NO - NO_TRADE title: Recommendation description: Actionable recommendation target_price: type: number maximum: 1 minimum: 0 title: Target Price description: Suggested entry price (0.0-1.0) edge: type: number title: Edge description: estimated_prob - market_price (positive = underpriced YES) confidence: type: number maximum: 1 minimum: 0 title: Confidence description: Confidence in the signal risk_rating: type: string enum: - low - medium - high title: Risk Rating description: Overall risk assessment size_pct: type: number maximum: 1 minimum: 0 title: Size Pct description: Kelly-derived position size as fraction of bankroll time_horizon: type: string title: Time Horizon description: 'Expected resolution: ''hours'', ''days'', ''weeks''' hedge: anyOf: - type: string - type: 'null' title: Hedge description: Suggested hedge, e.g. 'Buy NO on KXFED-26MAR19 at 0.82' causal: anyOf: - $ref: '#/components/schemas/CausalDecomposition' - type: 'null' description: Causal decomposition (?expand=causal) freshness: anyOf: - type: string enum: - fresh - stale - expired - type: 'null' title: Freshness description: Data freshness of the underlying analysis generated_at: type: string format: date-time title: Generated At description: When this signal was produced expires_at: type: string format: date-time title: Expires At description: Signal staleness window — do not trade after this time type: object required: - platform - market_id - title - recommendation - target_price - edge - confidence - risk_rating - size_pct - time_horizon - expires_at title: Signal description: |- Actionable trading signal with position sizing. The core product — everything needed to execute a trade. example: confidence: 0.82 edge: 0.09 expires_at: '2026-03-22T14:30:00Z' generated_at: '2026-03-21T14:30:00Z' market_id: KXFED-26MAR19 platform: kalshi recommendation: BUY_YES risk_rating: low size_pct: 0.035 target_price: 0.62 time_horizon: days title: Will the Fed cut rates at the March 2026 meeting? HTTPValidationError: properties: detail: items: $ref: '#/components/schemas/ValidationError' type: array title: Detail type: object title: HTTPValidationError CausalDecomposition: properties: overall_probability: type: number maximum: 1 minimum: 0 title: Overall Probability description: Aggregated probability from factor weights overall_confidence: type: number maximum: 1 minimum: 0 title: Overall Confidence description: Weighted confidence across all factors factors: items: $ref: '#/components/schemas/CausalFactor' type: array title: Factors description: Causal factors (typically 3-7) method: type: string title: Method description: 'Aggregation method: weighted_bayesian, linear, log_odds' default: weighted_bayesian generated_at: type: string format: date-time title: Generated At description: When this decomposition was produced type: object required: - overall_probability - overall_confidence - factors title: CausalDecomposition description: |- Weighted causal decomposition of a market probability estimate. Breaks a probability estimate into evidence-backed factors with Bayesian prior/posterior updates. example: factors: - claim: Inflation is within Fed's comfort zone confidence: 0.9 direction: supports_yes evidence: - 'PCE Feb 2026: 2.1%' - Core CPI declining 3 months posterior: 0.82 prior: 0.6 weight: 0.35 - claim: Fed rhetoric is dovish confidence: 0.75 direction: supports_yes evidence: - Waller speech March 12 - 'Bostic: ''open to adjustment''' posterior: 0.68 prior: 0.5 weight: 0.3 - claim: Tariff uncertainty creates headwinds confidence: 0.6 direction: supports_no evidence: - New tariffs announced March 5 - Trade deficit widening posterior: 0.45 prior: 0.4 weight: 0.2 generated_at: '2026-03-21T12:00:00Z' method: weighted_bayesian overall_confidence: 0.82 overall_probability: 0.71 ValidationError: properties: loc: items: anyOf: - type: string - type: integer type: array title: Location msg: type: string title: Message type: type: string title: Error Type input: title: Input ctx: type: object title: Context type: object required: - loc - msg - type title: ValidationError CausalFactor: properties: claim: type: string title: Claim description: The factor statement, e.g. 'Fed will hold rates' direction: type: string enum: - supports_yes - supports_no - neutral title: Direction description: Whether this factor pushes toward YES or NO resolution weight: type: number maximum: 1 minimum: 0 title: Weight description: Relative importance weight (top-level factors sum to ~1.0) confidence: type: number maximum: 1 minimum: 0 title: Confidence description: Confidence in this specific factor (0=uncertain, 1=certain) prior: type: number maximum: 1 minimum: 0 title: Prior description: Prior probability (base rate) posterior: type: number maximum: 1 minimum: 0 title: Posterior description: Updated probability after evidence (Bayesian posterior) evidence: items: type: string type: array title: Evidence description: Key evidence supporting this factor type: object required: - claim - direction - weight - confidence - prior - posterior title: CausalFactor description: A single factor in a causal decomposition. example: claim: Inflation is within Fed's comfort zone confidence: 0.9 direction: supports_yes evidence: - 'PCE Feb 2026: 2.1% (below 2.5% target ceiling)' - Core CPI declining for 3 consecutive months posterior: 0.82 prior: 0.6 weight: 0.35 ````