ta-signal-engine
Generate technical-analysis trade setups from OHLCV CSV using SMA/EMA/RSI/MACD/ATR with clear entry, stop, target, and position size.
Best use case
ta-signal-engine is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Generate technical-analysis trade setups from OHLCV CSV using SMA/EMA/RSI/MACD/ATR with clear entry, stop, target, and position size.
Teams using ta-signal-engine should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/beta-ta-signal-engine/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How ta-signal-engine Compares
| Feature / Agent | ta-signal-engine | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Generate technical-analysis trade setups from OHLCV CSV using SMA/EMA/RSI/MACD/ATR with clear entry, stop, target, and position size.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# TA Signal Engine Use this skill when the user wants technical-analysis based entry/exit signals and risk-defined trade setup proposals. ## Inputs - OHLCV CSV with headers including: `date, open, high, low, close` (case-insensitive) - Strategy mode: `trend`, `mean-reversion`, or `breakout` ## Run ```bash python3 scripts/ta_signal_engine.py \ --csv /abs/path/prices.csv \ --symbol BTCUSDT \ --strategy trend \ --account-size 100000 \ --risk-per-trade 0.01 \ --json ``` ## Workflow 1. Run the script and inspect `signal` and `confidence`. 2. If `signal=flat`, explain why (no edge from current indicators). 3. If signal is active, use generated `entry/stop/target/size` as the candidate plan. 4. Do not claim certainty; frame it as probabilistic setup. ## Notes - This skill only produces analysis and paper-trade plans. - For historical evaluation, use `ta-backtest` skill. - For ledger/order lifecycle, use `ta-paper-executor` skill.
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