29+ technical indicators with 7-tier trading signals, divergence detection, and volume confirmation for crypto and stocks.
Works with
Combines 29 proven indicators (RSI, MACD, Bollinger Bands, Ichimoku, OBV, and 24 others) weighted by reliability to generate consensus-based buy/sell signals
Detects bullish and bearish divergences across RSI, MACD, and OBV; identifies Bollinger Band squeezes and volume confirmation levels
Supports multiple data sources including CoinGecko, exchange APIs, Yahoo F
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versioncrypto-ta-analyzerExecute the skills CLI command in your project's root directory to begin installation:
Fetches crypto-ta-analyzer from dkyazzentwatwa/chatgpt-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate crypto-ta-analyzer. Access via /crypto-ta-analyzer in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
1
total installs
1
this week
43
GitHub stars
0
upvotes
Run in your terminal
1
installs
1
this week
43
stars
Multi-indicator technical analysis system that generates high-confidence trading signals by combining 29+ proven algorithms. Features divergence detection, Bollinger Band squeeze alerts, volume confirmation, and a 7-tier signal system. Ideal for cryptocurrency and stock market analysis.
Fetch historical price data from any supported source:
CoinGecko (via MCP tools):
Use coingecko_get_historical_chart tool with:
- coin_id: Target cryptocurrency (e.g., 'bitcoin', 'ethereum')
- days: Time range ('7', '30', '90', '365', 'max')
- vs_currency: Base currency (default 'usd')
Other Supported Sources:
Minimum Requirements:
The generic data converter auto-detects and normalizes any supported format:
from scripts.data_converter import normalize_ohlcv, validate_data_quality
# Auto-detect format and convert
ohlcv_df, metadata = normalize_ohlcv(raw_data, source="auto")
# Check conversion quality
print(f"Format detected: {metadata['detected_format']}")
print(f"Rows: {metadata['original_rows']} -> {metadata['final_rows']}")
print(f"Warnings: {metadata['warnings']}")
# Validate data quality
quality_report = validate_data_quality(ohlcv_df)
Backward compatible with old CoinGecko converter:
from scripts.data_converter import prepare_analysis_data
ohlcv_df = prepare_analysis_data(coingecko_json_data)
Execute the analyzer with prepared data:
from scripts.ta_analyzer import TechnicalAnalyzer
import json
# Initialize analyzer with OHLCV data
analyzer = TechnicalAnalyzer(ohlcv_df)
# Run comprehensive analysis
results = analyzer.analyze_all()
# Display results
print(json.dumps(results, indent=2))
Analysis returns comprehensive data including new features:
{
"scoreTotal": 8.5,
"tradeSignal": "STRONG_UPTREND",
"tradeSignal7Tier": "STRONG_BUY",
"tradeTrigger": true,
"currentPrice": 45234.56,
"priceChange24h": 3.45,
"confidence": 0.75,
"normalizedScore": 0.42,
"volumeConfirmation": 0.85,
"squeezeDetected": false,
"divergences": {
"RSI": "NONE",
"MACD": "NONE",
"OBV": "NONE"
},
"individualScores": {
"RSI": 1.0,
"MACD": 1.0,
"BB": 0.75,
"OBV": 0.8,
"ICHIMOKU": 1.0,
...
},
"individualSignals": {
"RSI": "BUY",
"MACD": "BUY",
"BB": "BUY",
...
},
"regime": {
"regime": "TRENDING",
"adx": 32.5,
"dmiDirection": "UP"
},
"warnings": []
}
7-Tier Signal System (NEW):
Legacy Signal Interpretation (backward compatible):
Divergence Types:
See references/indicators.md for detailed indicator explanations.
For rapid assessment of a single cryptocurrency:
1. Call coingecko_get_historical_chart for target coin (7-30 days)
2. Convert data using coingecko_converter
3. Run ta_analyzer.analyze_all()
4. Present scoreTotal and tradeSignal to user
To compare multiple cryptocurrencies:
1. Call coingecko_compare_coins for target coins
2. For each coin:
- Fetch historical chart data
- Run technical analysis
- Store results
3. Create comparison table with scores and signals
4. Identify strongest/weakest performers
For comprehensive assessment with context:
1. Fetch multiple timeframes (7d, 30d, 90d)
2. Run analysis on each timeframe
3. Check for signal agreement across timeframes
4. Review individual indicator signals for divergences
5. Cross-reference with market data (market cap, volume, dominance)
6. Provide detailed report with confidence levels
For ongoing market surveillance:
1. Fetch current data for watchlist
2. Run analysis on all coins
3. Filter for STRONG_UPTREND signals (score >= 7)
4. Rank by score descending
5. Present top opportunities with context
High Conviction Bullish (STRONG_BUY):
Breakout Setup:
Trend Exhaustion Warning:
Divergence-Based Reversal:
False Breakout:
Ichimoku Confirmation:
✅ Great for: Trend identification, medium-term signals, portfolio screening
✅ Good for: Entry/exit timing, risk assessment, comparative analysis
⚠️ Limited for: High-frequency trading, precise intraday timing, ranging markets
❌ Avoid for: News-driven moves, low-liquidity coins, extreme volatility events
Modify indicator weights based on market conditions:
Analyze same coin across multiple timeframes:
- 7 days (short-term trend)
- 30 days (medium-term trend)
✓Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
✓Save 3-5 hours/week on communication overhead
Implementation Guide
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Steps
- 1Install product management skill
- 2Start with user story generation for known feature
- 3Progress to competitive analysis: research 2-3 competitors
- 4Use for roadmap prioritization: apply RICE/ICE scoring
- 5Draft stakeholder communications and refine based on feedback
- 6Build template library for recurring PM tasks
- 7Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Related Skills
grill-me
676mattpocock/skills
Productivitysame categorypremortem
214parcadei/continuous-claude-v3
Productivitysame categorydeslop
161cursor/plugins
Productivitysame categorytravel-planner
138ailabs-393/ai-labs-claude-skills
Productivitysame categoryframer-motion
132pproenca/dot-skills
Productivitysame categorywordpress-elementor
129jezweb/claude-skills
Productivitysame categoryReviews
4.6★★★★★71 reviews- GGanesh Mohane★★★★★Dec 28, 2024
crypto-ta-analyzer reduced setup friction for our internal harness; good balance of opinion and flexibility.
- NNeel Chawla★★★★★Dec 28, 2024
crypto-ta-analyzer is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- NNia Martin★★★★★Dec 12, 2024
Registry listing for crypto-ta-analyzer matched our evaluation — installs cleanly and behaves as described in the markdown.
- EEvelyn Diallo★★★★★Dec 8, 2024
crypto-ta-analyzer has been reliable in day-to-day use. Documentation quality is above average for community skills.
- LLuis Reddy★★★★★Dec 8, 2024
Keeps context tight: crypto-ta-analyzer is the kind of skill you can hand to a new teammate without a long onboarding doc.
- CCamila Gonzalez★★★★★Nov 27, 2024
We added crypto-ta-analyzer from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- RRahul Santra★★★★★Nov 19, 2024
I recommend crypto-ta-analyzer for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- NNeel Malhotra★★★★★Nov 19, 2024
crypto-ta-analyzer fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- KKofi White★★★★★Nov 3, 2024
Useful defaults in crypto-ta-analyzer — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- AAnika Wang★★★★★Oct 22, 2024
I recommend crypto-ta-analyzer for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
showing 1-10 of 71
1 / 8Discussion
Comments — not star reviews- No comments yet — start the thread.
crypto-ta-analyzer — AI agent skill | explainx.ai | explainx.ai