What problem does it solve?
Coding agents often repeat the same mistakes across sessions because there is no systematic way to capture lessons learned from errors, analyze their root causes, and apply fixes to project rules, documentation, and hooks to prevent recurrence. This skill eliminates that gap by turning session failures into permanent, shared improvements for all team agents.
Core Features & Use Cases
- Root Cause Analysis & Lesson Extraction: Automatically scans coding agent session logs for failures, corrections, and repeated errors, requiring a minimum 3-layer "why" analysis to identify actionable root causes instead of just treating surface symptoms.
- Cross-Agent Improvement Application: Integrates with the multiagent-setup skill to apply extracted lessons to project rules, documentation, hooks, or custom skills, ensuring Claude Code, Codex, and GitHub Copilot all benefit from past mistakes.
- Automated Workflow Guardrails: Includes configurable hooks that block git commits if unextracted session activity exists, inject pending lessons into agent context at session start, and mark unextracted sessions with sentinel files to enforce the improvement cycle.
- Use Case: For a development team using multiple coding agents, if an agent repeatedly makes path resolution errors when editing skill files, this skill captures the root cause (missing path-specific rules), creates a targeted rule in
.agents/rules/, and ensures all future agents avoid the same mistake.
Quick Start
Use the kaizen skill to extract lessons from your latest coding session and apply any pending improvements to your project's rules and documentation.