orderflow-analysis

Orderflow Analysis Skill

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Install skill "orderflow-analysis" with this command: npx skills add saanjaypatil78/trading-platform/saanjaypatil78-trading-platform-orderflow-analysis

Orderflow Analysis Skill

Detects institutional trading patterns from Level 2 market data and trade executions.

Capabilities

This skill enables the agent to:

  • Analyze L2 orderbook depth for bid/ask walls

  • Detect absorption patterns (hidden liquidity)

  • Detect exhaustion at support/resistance

  • Identify imbalance sweeps

  • 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")

  1. Monitor Orderbook State

Track bid/ask walls and imbalance ratios. Call: get_orderbook_state(symbol: str) -> returns current book snapshot

  1. Run Detection Algorithms

When sufficient data is collected:

Call: analyze_footprint(symbol: str, window_seconds: int) Returns: List[FootprintSignal] with pattern type, direction, confidence

  1. 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

  1. 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

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)

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