Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
Complete workflow orchestration skill with plan node, self-improvement loop, and custom hooks integration
What This Skill Does
Structured workflow system for task planning, bug fixing, and self-improvement. Covers plan-first task management, subagent delegation, and a lessons capture system with metadata that tracks recurring mistake patterns. Designed for AI agents working on multi-step or architectural tasks.
The structured lessons format with recurrence tracking and priority metadata catches repeated mistakes that plain task lists or ad-hoc notes miss.
When to use it
- Starting a new project with a written spec before writing any code
- Logging a correction after a mistake to prevent it from recurring
- Fixing a reported bug autonomously without asking the user for steps
- Tracking command failures and API errors across sessions for diagnosis
- Running verification gates before marking a task complete
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Fix the authentication bug causing 401 errors on the /api/profile endpoint
- 1Enter plan mode and write a spec to tasks/todo.md listing investigation steps and acceptance criteria
- 2Check logs, error messages, and failing tests autonomously to identify the root cause
- 3Implement the minimal fix, touching only the necessary code paths
- 4Run tests and verify the endpoint returns 200 with valid credentials
- 5Update tasks/lessons.md with a structured lesson entry if a correction was made during the process
Bug fixed and verified against acceptance criteria, lessons logged with Priority, Area, and Pattern-Key metadata for future reference