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@ai-analytics-hub/cohort-analysis-skill

v1.0.1

Published

Install the AI Analytics Hub cohort retention analysis skill into your Cursor environment

Readme

cohort-analysis-skill

Install the AI Analytics Hub Cohort Retention Analysis skill into your Cursor environment with one command.

Install

Navigate to your Cursor project root, then run:

npx @ai-analytics-hub/cohort-analysis-skill

That's it. The skill is installed at .cursor/skills/cohort-analysis/.

What gets installed

.cursor/skills/cohort-analysis/
├── SKILL.md               # Skill instructions for Claude
├── cohort_analysis.py     # Canonical computation script
└── cohort_dashboard.html  # Interactive dashboard template

Usage

Once installed, open your project in Cursor and ask Claude:

"Run a cohort retention analysis on my data"

Claude will guide you through:

  1. Connecting your data — CSV file, Supabase MCP, or direct SQL connection
  2. Clarifying the analysis — segments, cohort definition, retention method
  3. Running the computation — via cohort_analysis.py
  4. Reviewing the results — with an explicit checkpoint before generating the dashboard
  5. Building the dashboard — an interactive HTML file with retention curves, segment breakdowns, and a cohort heatmap

Data sources supported

| Source | How | |--------|-----| | CSV file | Upload or provide a file path | | Supabase MCP | Claude queries directly — no credentials needed | | PostgreSQL | SQLAlchemy connection string | | Snowflake | SQLAlchemy connection string | | BigQuery | SQLAlchemy connection string | | MySQL | SQLAlchemy connection string |

Requirements

  • Cursor with Claude enabled
  • Python 3.8+ (for the computation script)
  • For SQL sources: pip install sqlalchemy + the relevant DB driver
  • For MCP sources: MCP server configured in Cursor — no extra packages needed

Update

Re-run the same command to overwrite with the latest version:

npx @ai-analytics-hub/cohort-analysis-skill@latest

About

Built by AI Analytics Hub — helping data teams build systematic AI workflows.