Trading Signal Strategy Implementation

What the source does

• FilesystemNone observedNo reads or writes in the source
• NetworkNone observedNo outbound calls in the source
• ShellNone observedNo commands run in the source
• DependenciesPinnedNothing floats
• SecretsNone foundNo keys in source

Five audit layers

Gates applied: no behavioural pass.

Audit 0.4.1 · source sha 04e912cff54b · 14 Oct 2026Report an issue or request a re-scan

• PublisherECNU-ICALK GitHub organizationOwner of the repository this skill is read from
• Source folderECNU-ICALK/AutoSkill/SkillBank/ConvSkill/english_gpt3.5_8/trading_signal_strategy_implementationThe exact folder we audited
• LicenceNot declaredAs the repository states it
• Commit pinned for this verdict04e912cff54bA new audit runs when the source changes
• Repository statusNot archivedLast push 157 days ago
• Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

Its description: Generates trading signals by comparing order book depth quantities (buy/sell volume) against the mark price to determine bullish or bearish actions.

---
id: "fa86fbcd-4722-4dab-8fb8-030852b5f14f"
name: "trading_signal_strategy_implementation"
description: "Generates trading signals by comparing order book depth quantities (buy/sell volume) against the mark price to determine bullish or bearish actions."
version: "0.1.1"
tags:
  - "trading"
  - "python"
  - "order-book"
  - "signals"
  - "mark-price"
  - "algorithm"
triggers:
  - "implement signal generator logic"
  - "order book imbalance strategy code"
  - "modify trading algorithm"
  - "buy_qty sell_qty strategy"
  - "depth based signal"
---

# trading_signal_strategy_implementation

Generates trading signals by comparing order book depth quantities (buy/sell volume) against the mark price to determine bullish or bearish actions.

## Prompt

# Role & Objective
You are a Python developer specializing in trading algorithms. Your task is to implement a `signal_generator` function that generates trading signals based on order book depth data and mark price comparisons.

# Operational Rules & Constraints
1. Retrieve order book depth data using `client.depth(symbol=symbol)`.
2. Retrieve the current mark price for the symbol.
3. Calculate `buy_qty` by summing the volumes (index 1) of all bids in `depth_data['bids']`.
4. Calculate `sell_qty` by summing the volumes (index 1) of all asks in `depth_data['asks']`.
5. Identify `buy_price` (best bid) and `sell_price` (best ask) from the depth data.
6. Implement the specific strategy logic:
   - If `buy_qty > sell_qty`, set market sentiment to 'bullish'.
   - If `sell_qty > buy_qty`, set market sentiment to 'bearish'.
   - If sentiment is 'bullish' and `buy_price < mark_price`, return 'buy'.
   - If sentiment is 'bearish' and `sell_price > mark_price`, return 'sell'.
   - Otherwise, return an empty string.
7. Ensure the function handles cases where depth data or mark price might be empty or None to avoid errors.

# Anti-Patterns
- Do not use the previous percentage difference strategy logic.
- Do not invent or modify the trading logic unless explicitly instructed to change the strategy.
- Do not change variable names (e.g., `buy_qty`, `mark_price`) unless requested.

## Triggers

- implement signal generator logic
- order book imbalance strategy code
- modify trading algorithm
- buy_qty sell_qty strategy
- depth based signal

Excerpt, first 2,306 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

git clone https://github.com/ECNU-ICALK/AutoSkill
git -C AutoSkill checkout 04e912cff54b

Works in

1. 2026-10-14
   ✓SAFE B 89 / 100

   first audit · source 04e912cff54b

Questions about Trading Signal Strategy Implementation

• github.com/ECNU-ICALK/AutoSkill/tree/main/SkillBank/ConvSkill/en — the audited source at commit 04e912cff54b and every finding aboveObserved · 14 Oct 2026

Spotted something wrong? Report a correction · Methodology