Expert quantitative finance, algorithmic trading, and financial data analysis using Python scientific computing.
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
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
Submit your Claude Code skill and start earning
epx add 404kidwiz/claude-supercode-skills --skill quant-analystCompatible with
Supported agents
Covers algorithmic trading strategy development, backtesting frameworks, and signal generation with walk-forward validation to prevent overfitting
Implements risk models including VaR, CVaR, Greeks calculations, and Monte Carlo simulations for derivatives pricing
Provides portfolio optimization techniques (mean-variance, Black-Litterman, risk parity) with transaction cost
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionquant-analystExecute the skills CLI command in your project's root directory to begin installation:
epx add 404kidwiz/claude-supercode-skills --skill quant-analystFetches quant-analyst from 404kidwiz/claude-supercode-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:
.cursor/skills/quant-analyst
Restart Cursor to activate quant-analyst. Access via /quant-analystin your agent's command palette.
Learn more:View source on GitHubSkills CLI docsAbout CursorWhat are agent skills?
Time estimate: 30-60 minutes to see productivity improvements
Prerequisites
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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Keeps context tight: quant-analyst is the kind of skill you can hand to a new teammate without a long onboarding doc.
We added quant-analyst from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Useful defaults in quant-analyst — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Useful defaults in quant-analyst — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend quant-analyst for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
quant-analyst is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Registry listing for quant-analyst matched our evaluation — installs cleanly and behaves as described in the markdown.
Keeps context tight: quant-analyst is the kind of skill you can hand to a new teammate without a long onboarding doc.
quant-analyst has been reliable in day-to-day use. Documentation quality is above average for community skills.
quant-analyst has been reliable in day-to-day use. Documentation quality is above average for community skills.
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