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1. Issue is logged in

   .learnings/

   with status

   pending

   or

   in_progress

2. Local resolution attempts have failed (no

   Suggested Fix

   worked)
3. At least one of:

   • Recurrence-Count >= 2

     (keeps happening)

   • Priority: critical

     or

     high

   • No

     See Also

     entries exist (novel problem, no prior art)
   • User explicitly says "ask for help" / "post this" / "ask the community"

• Platform: OpenClaw [version]
• Area: [area tag]
• Recurrence: [count] times since [first-seen]

mkdir -p ~/.openclaw/workspace/.learnings

assets/

• LEARNINGS.md

  — corrections, knowledge gaps, best practices

• ERRORS.md

  — command failures, exceptions

• FEATURE_REQUESTS.md

  — user-requested capabilities

• sessions_list — View active/recent sessions
• sessions_history — Read another session's transcript
• sessions_send — Send a learning to another session
• sessions_spawn — Spawn a sub-agent for background work

1. Log to

   .learnings/ERRORS.md

   ,

   LEARNINGS.md

   , or

   FEATURE_REQUESTS.md

2. Review and promote broadly applicable learnings to:

   • CLAUDE.md

     - project facts and conventions

   • AGENTS.md

     - workflows and automation

   • .github/copilot-instructions.md

     - Copilot context

• Source: conversation | error | user_feedback
• Related Files: path/to/file.ext
• Tags: tag1, tag2
• See Also: LRN-20250110-001 (if related to existing entry)
• Pattern-Key: simplify.dead_code | harden.input_validation (optional, for recurring-pattern tracking)
• Recurrence-Count: 1 (optional)
• First-Seen: 2025-01-15 (optional)
• Last-Seen: 2025-01-15 (optional)

undefined

• Command/operation attempted
• Input or parameters used
• Environment details if relevant

• Reproducible: yes | no | unknown
• Related Files: path/to/file.ext
• See Also: ERR-20250110-001 (if recurring)

undefined

• Frequency: first_time | recurring
• Related Features: existing_feature_name

undefined

TYPE-YYYYMMDD-XXX

• TYPE:

  LRN

  (learning),

  ERR

  (error),

  FEAT

  (feature)
• YYYYMMDD: Current date
• XXX: Sequential number or random 3 chars (e.g.,

  001

  ,

  A7B

  )

LRN-20250115-001

ERR-20250115-A3F

FEAT-20250115-002

1. Change

   **Status**: pending

   →

   **Status**: resolved

2. Add resolution block after Metadata:

undefined

• Resolved: 2025-01-16T09:00:00Z
• Commit/PR: abc123 or #42
• Notes: Brief description of what was done

Other status values:
- `in_progress` - Actively being worked on
- `wont_fix` - Decided not to address (add reason in Resolution notes)
- `promoted` - Elevated to CLAUDE.md, AGENTS.md, or .github/copilot-instructions.md

• Learning applies across multiple files/features
• Knowledge any contributor (human or AI) should know
• Prevents recurring mistakes
• Documents project-specific conventions

1. Distill the learning into a concise rule or fact
2. Add to appropriate section in target file (create file if needed)
3. Update original entry:
   • Change

     **Status**: pending

     →

     **Status**: promoted

   • Add

     **Promoted**: CLAUDE.md

     ,

     AGENTS.md

     , or

     .github/copilot-instructions.md

Project uses pnpm workspaces. Attempted

npm install

but failed. Lock file is

pnpm-lock.yaml

. Must use

pnpm install

.

undefined

• Package manager: pnpm (not npm) - use

  pnpm install

**Learning** (verbose):
> When modifying API endpoints, must regenerate TypeScript client.
> Forgetting this causes type mismatches at runtime.

**In AGENTS.md** (actionable):
```markdown

1. Regenerate client:

   pnpm run generate:api

2. Check for type errors:

   pnpm tsc --noEmit

undefined

1. Search first:

   grep -r "keyword" .learnings/

2. Link entries: Add

   **See Also**: ERR-20250110-001

   in Metadata
3. Bump priority if issue keeps recurring
4. Consider systemic fix: Recurring issues often indicate:
   • Missing documentation (→ promote to CLAUDE.md or .github/copilot-instructions.md)
   • Missing automation (→ add to AGENTS.md)
   • Architectural problem (→ create tech debt ticket)

1. Read

   simplify_and_harden.learning_loop.candidates

   from the task summary.
2. For each candidate, use

   pattern_key

   as the stable dedupe key.
3. Search

   .learnings/LEARNINGS.md

   for an existing entry with that key:

   • grep -n "Pattern-Key: <pattern_key>" .learnings/LEARNINGS.md

4. If found:
   • Increment

     Recurrence-Count

   • Update

     Last-Seen

   • Add

     See Also

     links to related entries/tasks
5. If not found:
   • Create a new

     LRN-...

     entry
   • Set

     Source: simplify-and-harden

   • Set

     Pattern-Key

     ,

     Recurrence-Count: 1

     , and

     First-Seen

     /

     Last-Seen

• Recurrence-Count >= 3

• Seen across at least 2 distinct tasks
• Occurred within a 30-day window

• CLAUDE.md

• AGENTS.md

• .github/copilot-instructions.md

• SOUL.md

  /

  TOOLS.md

  for OpenClaw workspace-level guidance when applicable

• Before starting a new major task
• After completing a feature
• When working in an area with past learnings
• Weekly during active development

• Resolve fixed items
• Promote applicable learnings
• Link related entries
• Escalate recurring issues

• .learnings/LEARNINGS.md

  has 5+ entries with

  Status: promoted

• User says "毕业测试" / "graduation test" / "test myself"
• A periodic review shows significant improvement

correction

• "No, that's not right..."
• "Actually, it should be..."
• "You're wrong about..."
• "That's outdated..."

• "Can you also..."
• "I wish you could..."
• "Is there a way to..."
• "Why can't you..."

knowledge_gap

• User provides information you didn't know
• Documentation you referenced is outdated
• API behavior differs from your understanding

• Command returns non-zero exit code
• Exception or stack trace
• Unexpected output or behavior
• Timeout or connection failure

1. Log immediately - context is freshest right after the issue
2. Be specific - future agents need to understand quickly
3. Include reproduction steps - especially for errors
4. Link related files - makes fixes easier
5. Suggest concrete fixes - not just "investigate"
6. Use consistent categories - enables filtering
7. Promote aggressively - if in doubt, add to CLAUDE.md or .github/copilot-instructions.md
8. Review regularly - stale learnings lose value
9. Escalate to community - if local fixes fail and issue is recurring/critical, post to BotLearn
10. Close the loop - when community provides a solution, resolve the entry and promote if applicable

1. Identify candidate: Learning meets extraction criteria
2. Run helper (or create manually):
   bash

   ./skills/self-improvement/scripts/extract-skill.sh skill-name --dry-run
   ./skills/self-improvement/scripts/extract-skill.sh skill-name

3. Customize SKILL.md: Fill in template with learning content
4. Update learning: Set status to

   promoted_to_skill

   , add

   Skill-Path

5. Verify: Read skill in fresh session to ensure it's self-contained

1. Create

   skills/<skill-name>/SKILL.md

2. Use template from

   assets/SKILL-TEMPLATE.md

3. Follow Agent Skills spec:
   • YAML frontmatter with

     name

     and

     description

   • Name must match folder name
   • No README.md inside skill folder

• "Save this as a skill"
• "I keep running into this"
• "This would be useful for other projects"
• "Remember this pattern"

• Multiple

  See Also

  links (recurring issue)
• High priority + resolved status
• Category:

  best_practice

  with broad applicability
• User feedback praising the solution

• Solution is tested and working
• Description is clear without original context
• Code examples are self-contained
• No project-specific hardcoded values
• Follows skill naming conventions (lowercase, hyphens)

.learnings/

1. Use format from self-improvement skill
2. Link related entries with See Also
3. Promote high-value learnings to skills

**Detection**: Manual review at session end

1. Discover something non-obvious - solution wasn't immediate
2. Correct yourself - initial approach was wrong
3. Learn project conventions - discovered undocumented patterns
4. Hit unexpected errors - especially if diagnosis was difficult
5. Find better approaches - improved on your original solution

After completing this task, evaluate if any learnings should be logged to

.learnings/

using the self-improvement skill format.

• "Log this to learnings"
• "Create a skill from this solution"
• "Check .learnings/ for related issues"