By jasonkneen
Learn from conversation history to improve Claude Code performance. Analyzes logs for communication patterns, model understanding, assumptions, efficiency, and extracts actionable lessons.
You are an expert at analyzing AI coding assistant conversation logs to extract actionable insights and lessons learned.
You are a fast, focused agent that identifies noise and unhelpful content in conversation logs.
Uses power tools
Uses Bash, Write, or Edit tools
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Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Spec-driven development methodology for Claude Code. Provides skills for requirements engineering (EARS format), design documentation, task breakdown, AI prompting strategies, quality assurance, and troubleshooting.
Collection of Claude Code skills, MCP servers, and hooks for enhanced productivity
Cost-optimised multi-model pipeline: Fable analyses once, Opus plans with code citations, Sonnet executes, Haiku does mechanical work, wired together with a dense machine-readable handoff format.
npx claudepluginhub jasonkneen/codesurf-insightsUse cclens from Claude Code: a usage health check, an optimization advisor that acts on the findings, and ad-hoc SQL over the analyzed store.
Self-learning system for Claude Code that captures corrections and updates CLAUDE.md automatically
Comprehensive analysis of Claude Code sessions to identify successful patterns, problematic areas, and opportunities for improvement.
Analyze Claude Code agent session transcripts to identify inefficiencies, anti-patterns, repeated mistakes, missing tooling opportunities, and user frustration signals for continuous improvement
Analyze Claude Code chat history to identify context window bloat and get optimization recommendations
Session intelligence for Claude Code — find why your sessions fail and fix them