Skill: austindixson/mulch-self-improving-agent (version 1.0.0)

--- name: self-improvement description: "Mulch Self Improver — Let your agents grow 🌱. Captures learnings with Mulch so expertise compounds across sessions. Use when: command/tool fails, user corrects you, missing feature, API fails, knowledge was wrong, or better approach found. Run mulch prime at session start; mulch record before finishing. Benefits: better and more consistent coding, improved experience, less hallucination." metadata: --- # Mulch Self Improver — Let your agents grow 🌱 Structured expertise that accumulates over time, lives in git, and works with any agent. Agents start each session from zero; the pattern discovered yesterday is forgotten today. This skill uses [Mulch](https://github.com/jayminwest/mulch): agents call `mulch record` to write learnings and `mulch query` to read them. Expertise compounds across sessions, domains, and teammates. **Mulch is a passive layer** — it does not contain an LLM. Agents use Mulch; Mulch does not use agents. **Benefits:** Better and more consistent coding · Improved experience · Less hallucination (grounding in project expertise) **When to use:** Command/tool fails, user corrects you, user wants a missing feature, your knowledge was wrong, or you found a better approach — record with Mulch and promote proven patterns to project memory. **Auto-detection:** The hook now detects errors and corrections automatically and prompts to record. **Mechanics:** One learning store — `.mulch/` (append-only JSONL, git-tracked, queryable). Session start: `mulch prime`. Recording: `mulch record <domain> --type <type> ...`. No `.learnings/` markdown files. **Qualification (features, benefits, pain points):** See [QUALIFICATION.md](QUALIFICATION.md). **Benchmark (token efficiency, troubleshooting skill improvement):** See [BENCHMARK.md](BENCHMARK.md) — e.g. ~54% fewer chars to get same resolutions; find rate same or better; less context → fewer tokens, less noise, lower risk of wrong fix. ## New Features (v1.1) ### Auto-Detection The hook now automatically detects learning moments: - **Errors/failures** — When commands fail or return errors - **Corrections** — When you say "no", "actually", "wrong", etc. - **Retries** — When you ask to try again The agent will prompt: "Want me to record this for next time?" ### Pre-loaded Domains 24 preset domains included in `config/domains.json`: ``` api, database, testing, frontend, backend, infra, docs, config, security, performance, deployment, auth, errors, debugging, workflow, customer, system, marketing, sales, content, competitors, crypto, automation, openclaw ``` ### Notifications When a learning is recorded, you're notified via Telegram. --- ## Quick Reference | Situation | Action | |-----------|--------| | Command/operation or API fails | `mulch record <domain> --type failure --description "..." --resolution "..."` | | User corrects you / knowledge was wrong | `mulch record <domain> --type convention "..."` or `--type pattern --name "..." --description "..."` | | Found better approach, best practice | `mulch record <domain> --type convention "..."` or `--type guide --name "..." --description "..."` | | Architectural or tech decision | `mulch record <domain> --type decision --title "..." --rationale "..."` | | Feature request (tracking) | `mulch record <domain> --type decision --title "..." --rationale "..."` | | Key file/endpoint to remember | `mulch record <domain> --type reference --name "..." --description "..."` | | Similar to existing record | Use `--relates-to <domain>:<id>` or `--supersedes`; run `mulch search "..."` first | | Broadly applicable pattern | Promote to `CLAUDE.md`, `AGENTS.md`, SOUL.md, TOOLS.md; use `mulch onboard` for snippets | | Session start (project has .mulch/) | Run `mulch prime` to load expertise into context | ## Mulch Setup **Install (optional; npx works without install):** ```bash npm install -g mulch-cli # or: npx mulch-cli <command> ``` **Initialize in project:** ```bash mulch init # Quick: add all preset domains at once cat config/domains.json | jq -r '.domains[].name' | xargs -I {} mulch add {} # Or add individually: mulch add api mulch add database mulch add testing # add domains that match your areas: frontend, backend, infra, docs, config ``` **Provider hooks (remind agent to record):** ```bash mulch setup cursor # or: claude, codex, gemini, windsurf, aider ``` **Onboarding snippet for AGENTS.md/CLAUDE.md:** ```bash mulch onboard ``` ## Record Types (Mulch) | Type | Required | Use Case | |------|----------|----------| | `failure` | description, resolution | What went wrong and how to avoid it | | `convention` | content | "Use pnpm not npm"; "Always WAL mode for SQLite" | | `pattern` | name, description | Named patterns, optional `--file` | | `decision` | title, rationale | Architecture, tech choices, feature tracking | | `reference` | name, description | Key files, endpoints, resources | | `guide` | name, description | Step-by-step procedures | Optional on any record: `--classification` (foundational | tactical | observational), `--tags`, `--relates-to`, `--supersedes`, `--evidence-commit`, `--evidence-file`, `--outcome-status` (success | failure). ## Workflow 1. **Session start:** If `.mulch/` exists, run `mulch prime` (or `mulch prime <domain>` for focus). 2. **During work:** When something fails or you learn something, run `mulch record <domain> --type <type> ...`. 3. **Before finishing:** Review; record any remaining insights with `mulch record`. 4. **Promote:** When a pattern is proven and broadly applicable, add to CLAUDE.md / AGENTS.md / SOUL.md / TOOLS.md; use `mulch onboard` to generate snippets. ## Finding Domain - Use existing domains from `mulch status` or `mulch query --all`. - Run `mulch learn` to get domain suggestions from changed files. - Common domains: `api`, `database`, `testing`, `frontend`, `backend`, `infra`, `docs`, `config`. ## Recurring Patterns and Linking - **Search first:** `mulch search "keyword"` or `mulch query <domain>`. - **Link records:** `mulch record ... --relates-to <domain>:<id>` or `--supersedes <domain>:<id>`. - Recurring issues → promote to CLAUDE.md/AGENTS.md or add to TOOLS.md/SOUL.md so all agents see them. ## Simplify & Harden Feed For candidates from the simplify-and-harden skill: 1. Use `pattern_key` as a stable tag: `mulch record <domain> --type pattern --name "<pattern_key>" --description "..." --tags "simplify-and-harden"`. 2. Search first: `mulch search "<pattern_key>"`; if found, use `--relates-to` or add to existing via `mulch edit` if needed. 3. When recurrence is high, promote to CLAUDE.md/AGENTS.md/SOUL.md/TOOLS.md as short prevention rules. ## Periodic Review - **When:** Before major tasks, after features, weekly. - **Commands:** `mulch status`, `mulch ready --since 7d`, `mulch query --all`. - **Actions:** Promote high-value records to project memory; run `mulch prune` for stale tactical/observational entries if desired; `mulch doctor --fix` for health. ## Promotion Targets | Learning Type | Promote To | |----------------|------------| | Behavioral patterns | `SOUL.md` (OpenClaw workspace) | | Workflow improvements | `AGENTS.md` | | Tool gotchas | `TOOLS.md` (OpenClaw workspace) | | Project facts, conventions | `CLAUDE.md` | | Copilot context | `.github/copilot-instructions.md` | Use `mulch onboard` to generate AGENTS.md/CLAUDE.md snippets. ## Detection Triggers **Record when you notice:** - User corrects you ("No, that's not right...", "Actually...") → convention or pattern - Command/API/tool fails → failure (description + resolution) - User wants missing capability → decision (title + rationale) - Your knowledge was wrong or outdated → convention - You found a better approach → convention or guide ## OpenClaw Setup OpenClaw injects workspace files; use Mulch for learnings. ### Installation ```bash clawdhub install self-improving-agent # or: git clone ... ~/.openclaw/skills/self-improving-agent ``` ### Workspace and Mulch - **Session start:** Run `mulch prime` when the project (or workspace) has `.mulch/`. Optionally add `mulch prime` output to workspace context if your setup supports it. - **Recording:** Use `mulch record` from the project or workspace directory that contains `.mulch/`. - **Promotion:** SOUL.md, AGENTS.md, TOOLS.md live in `~/.openclaw/workspace/`; add promoted rules there. ### Enable Hook (reminder at bootstrap) ```bash cp -r hooks/openclaw ~/.openclaw/hooks/self-improvement openclaw hooks enable self-improvement ``` See `references/openclaw-integration.md`. ## Generic Setup (Other Agents) 1. In project: `mulch init` and `mulch add <domain>` as needed. 2. Use `mulch setup <provider>` (cursor, claude, codex, etc.) for hooks. 3. Add to CLAUDE.md/AGENTS.md: "Run mulch prime at session start. Record learnings with mulch record <domain> --type failure|convention|decision|pattern|guide|reference." 4. Run `mulch onboard` and paste the snippet into your agent docs. ## Multi-Agent Safety Mulch is safe for concurrent use: advisory file locking, atomic writes, and `merge=union` in `.gitattributes` for JSONL. Multiple agents can run `mulch prime` and `mulch record` in parallel; locks serialize writes per domain. ## Skill Extraction When a Mulch record is valuable as a reusable skill: 1. Get content from `mulch query <domain>` or `mulch search "..."`. 2. Create `skills/<skill-name>/SKILL.md` (template in `assets/SKILL-TEMPLATE.md`). 3. Optionally note in the record (e.g. via `mulch edit`) that it was promoted to a skill. ## Best Practices 1. **Record immediately** — context is freshest after the issue. 2. **Pick the right type** — failure (description+resolution), convention (short rule), decision (title+rationale), etc. 3. **Use domains consistently** — e.g. same `api` domain for all API-related learnings. 4. **Link related records** — `--relates-to`, `--supersedes`. 5. **Run mulch prime at session start** — so the agent is grounded in existing expertise. 6. **Promote when proven** — move broadly applicable rules to CLAUDE.md, AGENTS.md, SOUL.md, TOOLS.md. ## No .learnings/ This skill does not use `.learnings/` or markdown log files. All learnings live in `.mulch/` and are recorded via the Mulch CLI. If you see references to `.learnings/` in older docs, treat them as superseded by Mulch.

path: _meta.json
content: {"ownerId":[REDACTED_SECRET],"slug":"mulch-self-improving-agent","version":"1.0.11","publishedAt":1771777713337}


Security scan verdicts — ClawScan: suspicious | static analysis:  | VirusTotal: malicious | SkillSpector: suspicious (CRITICAL)