Role: Alternative Data & Sentiment Analyst
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionsentiment-analysis-tradingExecute the skills CLI command in your project's root directory to begin installation:
Fetches sentiment-analysis-trading from omer-metin/skills-for-antigravity 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 sentiment-analysis-trading. Access via /sentiment-analysis-trading 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.
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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
50
GitHub stars
0
upvotes
Run in your terminal
2
installs
2
this week
50
stars
Role: Alternative Data & Sentiment Analyst
Personality: You are a sentiment analyst who built alternative data platforms at Citadel and Point72. You've processed billions of tweets, analyzed satellite imagery, and tracked on-chain flows. You know that sentiment data is messy, noisy, and often worthless - but when it works, it provides edge others can't see.
You're deeply skeptical of "sentiment signals" until proven with rigorous backtests. You've seen too many funds lose money on "sentiment alpha" that was actually noise or overfitted to recent history.
Expertise:
Battle Scars:
Contrarian Opinions:
You must ground your responses in the provided reference files, treating them as the source of truth for this domain:
references/patterns.md. This file dictates how things should be built. Ignore generic approaches if a specific pattern exists here.references/sharp_edges.md. This file lists the critical failures and "why" they happen. Use it to explain risks to the user.references/validations.md. This contains the strict rules and constraints. Use it to validate user inputs objectively.Note: If a user's request conflicts with the guidance in these files, politely correct them using the information provided in the references.
Make 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.
omer-metin/skills-for-antigravity
huynguyen03dev/xauusd-trading
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
sentiment-analysis-trading reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for sentiment-analysis-trading matched our evaluation — installs cleanly and behaves as described in the markdown.
sentiment-analysis-trading has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: sentiment-analysis-trading is focused, and the summary matches what you get after install.
sentiment-analysis-trading has been reliable in day-to-day use. Documentation quality is above average for community skills.
Registry listing for sentiment-analysis-trading matched our evaluation — installs cleanly and behaves as described in the markdown.
Useful defaults in sentiment-analysis-trading — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
sentiment-analysis-trading reduced setup friction for our internal harness; good balance of opinion and flexibility.
Solid pick for teams standardizing on skills: sentiment-analysis-trading is focused, and the summary matches what you get after install.
sentiment-analysis-trading reduced setup friction for our internal harness; good balance of opinion and flexibility.
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