Data-driven cryptocurrency trading strategies combining Binance market data, technical indicators, and sentiment analysis.
Works with
Integrates real-time and historical price/volume data from Binance with calculated TA indicators (SMA, RSI, MACD, Bollinger Bands, Stochastic)
Aggregates market sentiment from crypto RSS feeds to inform buy/sell/hold signals and entry/exit recommendations
Generates risk management guidance including stop-loss levels, position sizing (1-5% of capital), and volatil
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiontrading-strategistExecute the skills CLI command in your project's root directory to begin installation:
Fetches trading-strategist from kukapay/crypto-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 trading-strategist. Access via /trading-strategist 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
2
total installs
2
this week
17
GitHub stars
0
upvotes
Run in your terminal
2
installs
2
this week
17
stars
This skill generates data-driven trading strategies for cryptocurrencies by integrating multiple data sources and analytical tools.
/api/v3/ticker/price and /api/v3/ticker/24hr)/api/v3/klines with 30-100 days of data)Use the scripts/calculate_ta.py script to compute indicators from historical data.
Combine TA signals, price action, and sentiment score to recommend:
For ETH, generate a trading strategy based on current market data.
→ Fetch ETH data, calculate TA, get sentiment, output strategy.
Analyze BTC with 50-day history, include sentiment, recommend swing trade.
→ Use longer history, focus on swing signals.
scripts/calculate_ta.py: Python script for TA indicator calculationsscripts/fetch_binance.py: Helper for Binance API calls
./skills/trading-strategies/SKILL.mdMake data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
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parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
We added trading-strategist from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
trading-strategist is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
trading-strategist reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for trading-strategist matched our evaluation — installs cleanly and behaves as described in the markdown.
Solid pick for teams standardizing on skills: trading-strategist is focused, and the summary matches what you get after install.
Keeps context tight: trading-strategist is the kind of skill you can hand to a new teammate without a long onboarding doc.
trading-strategist fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added trading-strategist from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
trading-strategist has been reliable in day-to-day use. Documentation quality is above average for community skills.
trading-strategist has been reliable in day-to-day use. Documentation quality is above average for community skills.
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