orderflow-analysis

Original：🇺🇸 English

Translated

Skill for detecting institutional order flow patterns (absorption, exhaustion, imbalance, sweep) from L2 market depth and trade data.

2installs

Sourcesaanjaypatil78/trading-platform

Added on2026-02-07

NPX Install

npx skill4agent add saanjaypatil78/trading-platform orderflow-analysis

SKILL.md Content

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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")

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)