crypto-ta-analyzer

dkyazzentwatwa/chatgpt-skills

Multi-indicator technical analysis for crypto and market OHLCV data with trend, momentum, volume, and divergence signals.

Source View on skills.sh

What is crypto-ta-analyzer?

Runs deterministic technical analysis on OHLCV (open, high, low, close, volume) data using a bundled indicator stack. Use this when you need explicit trend, momentum, volume, and divergence signals rather than narrative market opinion.

Normalizes and converts OHLCV data from multiple source formats
Computes trend indicators to identify directional bias
Calculates momentum and oscillators for overbought/oversold conditions
Analyzes volume patterns and their relationship to price
Detects divergences between price and indicators
Scores and aggregates signals across the indicator stack

How to install crypto-ta-analyzer

npx skills add https://github.com/dkyazzentwatwa/chatgpt-skills --skill crypto-ta-analyzer

Prerequisites

Python environment with required dependencies for the analyzer scripts
OHLCV data in a supported format or access to a data source like CoinGecko

Claude Code

Cursor

Windsurf

Cline

How to use crypto-ta-analyzer

1.Obtain or retrieve OHLCV data for your target asset and timeframe
2.If data is not in standard format, use scripts/data_converter.py or scripts/coingecko_converter.py to normalize it
3.Run scripts/ta_analyzer.py with the normalized data to compute all indicators
4.Review the indicator outputs and signal scores to identify areas of agreement and conflict
5.Interpret results in context of current market regime, noting that indicators are deterministic but not predictive

Use cases

Good for

Analyzing historical crypto price data to identify trend changes and momentum shifts
Comparing multiple technical indicators on the same asset to find agreement or conflicts
Converting data from CoinGecko or other sources into standardized OHLCV format for analysis
Evaluating volume confirmation of price moves to assess signal strength
Detecting divergences between price action and momentum indicators

Who it's for

Traders and analysts performing technical analysis on crypto or traditional markets
Developers building trading bots or analysis tools that need deterministic indicator output
Researchers comparing indicator behavior across different market regimes

crypto-ta-analyzer FAQ

Should I treat indicator signals as guaranteed trading outcomes?

No. Signals are deterministic outputs from the indicator stack, but they do not guarantee future price movement. Always consider regime sensitivity, market context, and risk management.

What data formats does this skill support?

It works with OHLCV data. Use the included converter scripts (data_converter.py or coingecko_converter.py) to reshape data from other sources into the required format.

Can I use this for non-crypto markets?

Yes. The skill works on any market OHLCV data, not just cryptocurrency. The indicators and analysis approach are market-agnostic.

How do I interpret conflicting signals from different indicators?

Explain the disagreement in context: which indicators align, which diverge, and what that may suggest about market regime or signal strength. Avoid presenting a single number without this context.

Full instructions (SKILL.md)

Source of truth, from dkyazzentwatwa/chatgpt-skills.

name: crypto-ta-analyzer description: Run multi-indicator technical analysis on crypto or market OHLCV data. Use for deterministic trend, momentum, volume, and divergence analysis.

Crypto TA Analyzer

Use the bundled indicators when the user needs explicit technical analysis rather than a narrative market opinion.

Workflow

Get normalized OHLCV data first.
Use scripts/data_converter.py or scripts/coingecko_converter.py when source formats need reshaping.
Run scripts/ta_analyzer.py for the actual indicator stack and signal scoring.
Explain indicator agreement, conflicts, and regime sensitivity instead of presenting one number without context.

Guardrails

Do not present signals as guaranteed outcomes.
Keep the distinction clear between deterministic indicator output and discretionary interpretation.

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