analytics-skill
NewSkills library for product data scientists working with Claude
Summary
The analytics-skill provides a library of tools and patterns for product data scientists working with Claude, enabling efficient querying, analysis, and visualization of product data.
- It streamlines common analytics workflows such as cohort analysis, funnel conversion, and metric computation directly within Claude Code.
Install & Usage
mkdir -p .claude/skillsmkdir -p .claude/skills && curl -o .claude/skills/analytics-skill.md https://raw.githubusercontent.com/vermapragya/analytics-skill/main/SKILL.md/analytics-skillUse Cases
Usage Examples
/analytics-skill analyze funnel --events 'page_view, add_to_cart, purchase' --timeframe last_30_days
Run cohort analysis on user signups from January 2024 with weekly retention for 12 weeks.
Generate a product metrics report including DAU, retention rate, and revenue per user for last quarter.
Security Audits
Frequently Asked Questions
What is analytics-skill?
The analytics-skill provides a library of tools and patterns for product data scientists working with Claude, enabling efficient querying, analysis, and visualization of product data. It streamlines common analytics workflows such as cohort analysis, funnel conversion, and metric computation directly within Claude Code.
How to install analytics-skill?
To install analytics-skill: create the skills directory (mkdir -p .claude/skills), then run: mkdir -p .claude/skills && curl -o .claude/skills/analytics-skill.md https://raw.githubusercontent.com/vermapragya/analytics-skill/main/SKILL.md. Finally, /analytics-skill in Claude Code.
What is analytics-skill best for?
analytics-skill is a skill categorized under Data & Analytics. Created by vermapragya.
What can I use analytics-skill for?
analytics-skill is useful for: Run cohort retention analysis on user activity data to understand long-term engagement trends.; Compute funnel conversion rates across multiple steps like signup, activation, and purchase.; Generate automated weekly product metrics reports with key KPIs and visualizations.; Perform A/B test result analysis including statistical significance and effect size calculations.; Query and aggregate event data from product analytics platforms like Amplitude or Mixpanel.; Build custom dashboards for product health monitoring using predefined metric templates..