Showcase: claude-code-conversation-analyzer — analytics dashboard built on top of claude-code-log

Hi @daaain — first off, huge thanks for claude-code-log. The SQLite cache it produces (claude-code-log-cache.db) turned out to be the perfect substrate for a project I've been building, and I wanted to share it here in case it's interesting to you or other users of this tool.

What I built

claude-code-conversation-analyzer — a dashboard that reads the cclog SQLite DB and layers on:

• Cost analysis — per-session and per-model cost breakdowns using current Anthropic pricing (input/output/cache-creation/cache-read tokens)
• Quality scoring — weighted scoring across cache usage, conversation length, query specificity, context utilization, and prompt efficiency, with letter grades (A–F)
• Compaction detection — flags cache drops >10k tokens as compaction events
• Better UI — Next.js 16 + React 19 dashboard with:
  • Project overview grid with grade distribution
  • Conversation list with sortable metrics
  • Expandable conversation cards with token charts (Recharts) and message transcripts
  • Full-text search across projects and sessions
  • Dark/light theme

How it integrates with claude-code-log

The pipeline runs claude-code-log as the data-generation step, then augments the resulting SQLite DB with two extra tables (session_costs, session_quality). Nothing in the cclog DB itself is modified — the analyzer is purely additive. A make all target handles the full flow: clone/update cclog fork → regenerate transcripts → run analysis → serve dashboard.

This is a showcase rather than a requested code change. Review the linked claude-code-conversation-analyzer project and its make all pipeline, then determine whether the repository has a documented place for external integrations; done would be a clear, agreed presentation of the project's cclog and SQLite relationship.