Claude Code Insights

Unlock the hidden value in your Claude Code conversation history through automatic processing, semantic search, and intelligent insight generation.

Overview

This skill automatically analyzes your project's Claude Code conversations (stored in ~/.claude/projects/[project]/*.jsonl) to provide:

RAG-Powered Semantic Search: Find conversations by meaning, not just keywords
Automatic Insight Reports: Pattern detection, file hotspots, tool usage analytics
Activity Trends: Understand your development patterns over time
Knowledge Extraction: Surface recurring topics, solutions, and best practices
Zero Manual Effort: Fully automatic processing of existing conversations

When to Use This Skill

Trigger Phrases:

"Find conversations about [topic]"
"Generate weekly insights report"
"What files do I modify most often?"
"Launch the insights dashboard"
"Export insights as [format]"

Use Cases:

Search past conversations by topic or file
Generate activity reports and insights
Understand development patterns over time
Extract knowledge and recurring solutions
Visualize activity with interactive dashboard

NOT for:

Real-time conversation analysis (analyzes history only)
Conversations from other projects (project-specific)
Manual conversation logging (automatic only)

Response Style

Informative and Visual: Present search results with relevance scores and snippets. Generate reports with clear metrics and ASCII visualizations. Offer to save or export results.

Mode Selection

| User Request | Mode | Reference | |--------------|------|-----------| | "Find conversations about X" | Search | modes/mode-1-search.md | | "Generate insights report" | Insights | modes/mode-2-insights.md | | "Launch dashboard" | Dashboard | modes/mode-3-dashboard.md | | "Export as JSON/CSV/HTML" | Export | modes/mode-4-export.md |

Mode Overview

Mode 1: Search Conversations

Find past conversations using semantic search (by meaning) or metadata search (by files/tools). → Details: modes/mode-1-search.md

Mode 2: Generate Insights

Analyze patterns and generate reports with file hotspots, tool usage, and knowledge highlights. → Details: modes/mode-2-insights.md

Mode 3: Interactive Dashboard

Launch a Next.js web dashboard for rich visualization and exploration. → Details: modes/mode-3-dashboard.md

Mode 4: Export and Integration

Export insights as Markdown, JSON, CSV, or HTML for sharing and integration. → Details: modes/mode-4-export.md

Initial Setup

First time usage:

Install dependencies: pip install -r requirements.txt
Run initial processing (automatic on first use)
Build embeddings (one-time, ~1-2 min)
Ready to search and analyze!

What happens automatically:

Scans ~/.claude/projects/[current-project]/*.jsonl
Extracts and indexes conversation metadata
Builds vector embeddings for semantic search
Creates SQLite database for fast queries

Important Reminders

Automatic processing: Skill updates index on each use (incremental)
First run is slow: Embedding creation takes 1-2 minutes
Project-specific: Analyzes only current project's conversations
Dashboard requires Node.js: v18+ for the Next.js dashboard
ChromaDB for search: Vector similarity search for semantic queries

Limitations

Only analyzes JSONL conversation files from Claude Code
Requires sentence-transformers for embedding creation
Dashboard is local only (localhost:3000)
Large conversation histories may take longer to process initially

Reference Materials

| Resource | Purpose | |----------|---------| | modes/*.md | Detailed mode instructions | | reference/troubleshooting.md | Common issues and fixes | | scripts/ | Processing and indexing scripts | | dashboard/ | Next.js dashboard application |

Success Criteria

[ ] Conversations processed and indexed
[ ] Embeddings built for semantic search
[ ] Search returns relevant results
[ ] Insights reports generated correctly
[ ] Dashboard launches and displays data

Tech Stack: Python (processing), SQLite (metadata), ChromaDB (vectors), Next.js (dashboard)