Expert pandas data manipulation with vectorized operations, memory optimization, and production-grade validation patterns.
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 jeffallan/claude-skills --skill pandas-proCompatible with
Supported agents
Covers core workflows: data assessment, transformation design, efficient implementation, result validation, and memory profiling
Includes reference guides and code patterns for DataFrame operations, data cleaning, aggregation, merging, and time series resampling
Enforces vectorized operations over iteration, proper indexing with .loc[] / .iloc[] , and explicit mi
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionpandas-proExecute the skills CLI command in your project's root directory to begin installation:
epx add jeffallan/claude-skills --skill pandas-proFetches pandas-pro from jeffallan/claude-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/pandas-pro
Restart Cursor to activate pandas-pro. Access via /pandas-proin 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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I recommend pandas-pro for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
I recommend pandas-pro for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in pandas-pro — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend pandas-pro for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in pandas-pro — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Useful defaults in pandas-pro — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
pandas-pro has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: pandas-pro is focused, and the summary matches what you get after install.
pandas-pro has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: pandas-pro is focused, and the summary matches what you get after install.
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