--- name: orderflow-analysis description: Skill for detecting institutional order flow patterns (absorption, exhaustion, imbalance, sweep) from L2 market depth and trade data. --- # Orderflow Analysis Skill Detects institutional trading patterns from Level 2 market data and trade executions. ## Capabilities This skill enables the agent to: 1. Analyze L2 orderbook depth for bid/ask walls 2. Detect absorption patterns (hidden liquidity) 3. Detect exhaustion at support/resistance 4. Identify imbalance sweeps 5. Generate trade signals with confidence levels ## Prerequisites - Active L2 data connection (Alpaca Pro or Polygon) - Trading symbols configured in watchlist ## Procedural Steps ### 1. Connect to L2 Data Stream ``` Use the trading-orderflow MCP server to establish WebSocket connection. Call: connect_l2_stream(symbol: str, provider: "alpaca" | "polygon") ``` ### 2. Monitor Orderbook State ``` Track bid/ask walls and imbalance ratios. Call: get_orderbook_state(symbol: str) -> returns current book snapshot ``` ### 3. Run Detection Algorithms When sufficient data is collected: ``` Call: analyze_footprint(symbol: str, window_seconds: int) Returns: List[FootprintSignal] with pattern type, direction, confidence ``` ### 4. Interpret Signals | Signal Type | Description | Suggested Action | |-------------|-------------|------------------| | ABSORPTION | Heavy volume absorbed without price movement | Fade the volume direction | | EXHAUSTION | Declining volume at S/R | Prepare for reversal | | IMBALANCE | 3:1+ buy/sell ratio | Follow imbalance direction | | SWEEP | Multiple levels cleared rapidly | Momentum follow | ### 5. Forward to Confirmation Mesh All signals must pass through confirmation mesh before execution: ``` Call: validate_signal(signal: FootprintSignal, quantity: float) -> ConfirmationResult ``` ## Safety Guardrails - Never execute trades based on LOW confidence signals - Require L2 liquidity verification before market orders - All executions must go through confirmation_mesh validation - Circuit breakers halt trading after consecutive failures ## Example Workflow ```python # Agent detects high-confidence absorption signal = await analyze_footprint("AAPL", window_seconds=60) if signal.signal_type == "ABSORPTION" and signal.confidence == "HIGH": # Validate before execution result = await validate_signal(signal, quantity=100) if result.approved: # Proceed to execute-trade skill await execute_confirmed_trade(result) ```