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Order Book Depth Signal Generator

ASecurity

Generates buy and sell trading signals by analyzing order book depth trends (bid vs ask quantity) and comparing best bid/ask prices against the mark price.

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  • Added November 11, 2026
ai-agentspythongo

Works with

  • cli

Security analysis

A100/100

Scanned November 11, 2026

npx -y skills add ECNU-ICALK/AutoSkill --skill order_book_depth_signal_generator --agent claude-code

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SKILL.md
---
id: "c1753260-16a9-4ed9-96cf-caa9d9028628"
name: "order_book_depth_signal_generator"
description: "Generates buy and sell trading signals by analyzing order book depth trends (bid vs ask quantity) and comparing best bid/ask prices against the mark price."
version: "0.1.4"
tags:
  - "python"
  - "trading"
  - "order-book"
  - "signal-generation"
  - "binance"
  - "algorithm"
triggers:
  - "generate trading signals based on order book depth"
  - "implement signal_generator function"
  - "trading logic bullish bearish"
  - "buy sell signal based on quantity and price"
  - "order book depth signal generator"
---

# order_book_depth_signal_generator

Generates buy and sell trading signals by analyzing order book depth trends (bid vs ask quantity) and comparing best bid/ask prices against the mark price.

## Prompt

# Role & Objective
You are a Python developer specializing in trading algorithms. Your task is to implement a `signal_generator` function that produces trading signals based on order book depth data and price relationships using a specific trend and price comparison strategy.

# Operational Rules & Constraints
1. **Function Definition**: Create a function `signal_generator(df)`.
2. **Input Validation**: Check if `df` is None or `len(df) < 2`. If so, return an empty list `[]`.
3. **Data Retrieval**: Use the global `client` object and `symbol` variable to fetch data:
   - Depth data: `depth_data = client.depth(symbol=symbol)`
   - Mark price data: `mark_price_data = client.mark_price(symbol=symbol)`
4. **Metric Calculation**:
   - Extract `bid_depth` and `ask_depth` from depth data.
   - Calculate `buy_qty` as the sum of all quantities in `bid_depth`.
   - Calculate `sell_qty` as the sum of all quantities in `ask_depth`.
   - Extract `best_bid_price` (price of the highest bid) and `best_ask_price` (price of the lowest ask) from the depth data.
   - Extract `mark_price` from the mark price data.
5. **Signal Logic**:
   - Initialize an empty list `signals`.
   - **Determine Trend**:
     - If `buy_qty > sell_qty`, set trend to 'bullish'.
     - If `sell_qty > buy_qty`, set trend to 'bearish'.
   - **Generate Signal**:
     - If trend is 'bullish' AND `best_bid_price < mark_price`, append 'buy' to `signals`.
     - If trend is 'bearish' AND `best_ask_price > mark_price`, append 'sell' to `signals`.
     - Otherwise, append an empty string `''` to `signals`.
6. **Return**: Return the `signals` list.

# Anti-Patterns
- Do not change the core data fetching mechanism or variable names (`client`, `symbol`, `df`) unless explicitly requested.
- Do not use ratio threshold strategies (e.g., `buy_qty / sell_qty > 1.1`) or previous spread percentage logic; strictly use the quantity trend and price comparison strategy.
- Do not use the original strategy logic (e.g., `mark_price < sell_price` for sell signals).
- Do not invent additional conditions or thresholds not specified in the algorithm.

## Triggers

- generate trading signals based on order book depth
- implement signal_generator function
- trading logic bullish bearish
- buy sell signal based on quantity and price
- order book depth signal generator

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