Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
No user-facing changes in v1.0.5. - No file changes detected in this release. - Documentation and functionality remain unchanged.
What This Skill Does
Mulch captures agent learnings in an append-only, git-tracked store so expertise persists across sessions. Agents run `mulch prime` at session start to load existing knowledge, then use `mulch record` to save failures, conventions, patterns, and decisions as they work. Auto-detection hooks identify errors and user corrections automatically.
Unlike per-session agent memory, Mulch stores learnings in git so they persist across sessions, can be shared across teammates and agents, and accumulate without manual prompt file maintenance.
When to use it
- Recording the fix after an API call fails so the same error is not repeated next session
- Logging a user correction mid-session so the agent adopts the right convention going forward
- Loading accumulated project expertise into context at the start of a new session
- Tracking architectural decisions and their rationale across a team of agents
- Promoting a proven pattern to CLAUDE.md or AGENTS.md after multiple sessions confirm it
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: the same npm peer dependency error just failed again
- 1Run `mulch search "peer dependency"` to check if a resolution already exists
- 2Find no existing record, so run `mulch record config --type failure --description "npm install fails on peer deps" --resolution "Use --legacy-peer-deps flag"`
- 3Run `mulch prime` at the next session start to load this resolution into context
Learning stored in `.mulch/config.jsonl`; future sessions load it automatically so the agent avoids repeating the same failure
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.