Learning Quality Skill
This skill defines when and how to capture learnings during ClosedLoop runs.
Decision Tree: Should I Capture This?
Before writing a learning, run through this decision tree in order:
1. Did I make a mistake and correct it, or discover something non-obvious?
NO → Don't capture (no learnings event)
YES → Continue
2. Is it a config value? (specific URL, file path, project command, type name)
YES → Write to CLAUDE.md (project scope), not org-patterns
NO → Continue
3. Is it tied to a single feature/bug with no generalizable principle?
YES → SKIP
NO → Continue
4. Will it still be true in 6 months?
NO → SKIP (or generalize the principle)
YES → Continue
5. Does it already exist in org-patterns.toon or CLAUDE.md?
YES → SKIP (or note "Supersedes: [old pattern]" if correcting)
NO → CAPTURE IT
Note: Even "basic" knowledge is worth capturing if you actually made that mistake. These learnings exist because LLM agents struggle with certain patterns that humans might consider obvious. The goal is to help future agent runs avoid the same mistakes.
Hard Rejection Criteria
SKIP if ANY of these apply:
| Criterion | Example | Why |
|---|---|---|
| Specific URL/path/config | "Use https://github.com/org/repo" | Config, not principle → CLAUDE.md |
| Project-specific names | "Use MyProjectType not OtherType" | Belongs in CLAUDE.md |
| One-off bug fix | "Field X was null in row 123" | Not reusable |
| Already captured | (check pending/, CLAUDE.md, org-patterns.toon) | Avoid duplicates |
Note: Even patterns that seem like "basic knowledge" are worth capturing if you actually made that mistake. These learnings exist because LLM agents struggle with certain patterns. The goal is to help future agent runs avoid the same mistakes.
Capture Workflow
When you have a learning worth capturing:
Step 1: Classify Scope
| Scope | Destination | Heuristic |
|---|---|---|
| Project | CLAUDE.md | Mentions specific file paths, package names, or project-unique features |
| Global | org-patterns.toon | Applies to any project using the same language/framework/tool |
Step 2: Generalize if Needed
Extract the underlying principle, not the specific instance.
Test: Would this help someone working on a different feature?
Step 3: Write the Pattern
Formula: [When/Where] + [specific action] + [context]
Step 4: Check for Conflicts
Before writing:
- Check
$CLOSEDLOOP_WORKDIR/.learnings/pending/for learnings in this run - Check project CLAUDE.md "Learned Patterns" section
- Check
~/.closedloop-ai/learnings/org-patterns.toon
If contradiction exists (existing says "do X", new says "don't do X"):
- Verify which is correct based on evidence
- Capture only the correct one
- Add "Supersedes: [old pattern]" if correcting
Step 5: Write the File
Output location:
$CLOSEDLOOP_WORKDIR/.learnings/pending/{agent-name}-$CLOSEDLOOP_AGENT_ID.json
Format:
{
"what_happened": "Brief description of what occurred",
"why": "Root cause or reason this matters",
"fix_applied": "What you did to resolve it (if applicable)",
"pattern_to_remember": "The actionable takeaway (minimum 20 chars)",
"applies_to": ["agent-name"],
"context": {
"file": "relative/path/to/file.ext",
"line": 42,
"function": "function_name"
}
}
Use ["*"] for applies_to if the pattern applies to all agents.
No Learnings Event
If you completed work without learnings to capture:
{
"no_learnings": true,
"reason": "Task was straightforward with no new patterns discovered"
}
This is valid—not every task produces learnings.
Quick Reference
Worth Capturing (Durable + Non-Obvious)
- Non-obvious tool behaviors not in docs
- Project conventions not inferable from code
- Architectural decisions with non-obvious rationale
- Gotchas that cost time and aren't documented
Not Worth Capturing
| Category | Examples |
|---|---|
| Common knowledge | TS strict mode, git basics, debugging 101 |
| Config values | URLs, file paths, project commands |
| Implementation details | Query order, field names, styling choices |
| Temporary | Bug workarounds, feature-specific decisions |
Scope Decision
Mentions specific paths/packages/features? → Project (CLAUDE.md)
Applies to any project with same tech? → Global (org-patterns.toon)
Domain-Specific Guidance
Your agent definition may reference a domain-specific learning prompt (e.g., prompts/plan-writer-learning.md). If so, read it before capturing learnings.