compound-learnings
npx machina-cli add skill parcadei/Continuous-Claude-v3/compound-learnings --openclawCompound Learnings
Transform ephemeral session learnings into permanent, compounding capabilities.
When to Use
- "What should I learn from recent sessions?"
- "Improve my setup based on recent work"
- "Turn learnings into skills/rules"
- "What patterns should become permanent?"
- "Compound my learnings"
Process
Step 1: Gather Learnings
# List learnings (most recent first)
ls -t $CLAUDE_PROJECT_DIR/.claude/cache/learnings/*.md | head -20
# Count total
ls $CLAUDE_PROJECT_DIR/.claude/cache/learnings/*.md | wc -l
Read the most recent 5-10 files (or specify a date range).
Step 2: Extract Patterns (Structured)
For each learnings file, extract entries from these specific sections:
| Section Header | What to Extract |
|---|---|
## Patterns or Reusable techniques | Direct candidates for rules |
**Takeaway:** or **Actionable takeaway:** | Decision heuristics |
## What Worked | Success patterns |
## What Failed | Anti-patterns (invert to rules) |
## Key Decisions | Design principles |
Build a frequency table as you go:
| Pattern | Sessions | Category |
|---------|----------|----------|
| "Check artifacts before editing" | abc, def, ghi | debugging |
| "Pass IDs explicitly" | abc, def, ghi, jkl | reliability |
Step 2b: Consolidate Similar Patterns
Before counting, merge patterns that express the same principle:
Example consolidation:
- "Artifact-first debugging"
- "Verify hook output by inspecting files"
- "Filesystem-first debugging" → All express: "Observe outputs before editing code"
Use the most general formulation. Update the frequency table.
Step 3: Detect Meta-Patterns
Critical step: Look at what the learnings cluster around.
If >50% of patterns relate to one topic (e.g., "hooks", "tracing", "async"): → That topic may need a dedicated skill rather than multiple rules → One skill compounds better than five rules
Ask yourself: "Is there a skill that would make all these rules unnecessary?"
Step 4: Categorize (Decision Tree)
For each pattern, determine artifact type:
Is it a sequence of commands/steps?
→ YES → SKILL (executable > declarative)
→ NO ↓
Should it run automatically on an event (SessionEnd, PostToolUse, etc.)?
→ YES → HOOK (automatic > manual)
→ NO ↓
Is it "when X, do Y" or "never do X"?
→ YES → RULE
→ NO ↓
Does it enhance an existing agent workflow?
→ YES → AGENT UPDATE
→ NO → Skip (not worth capturing)
Artifact Type Examples:
| Pattern | Type | Why |
|---|---|---|
| "Run linting before commit" | Hook (PreToolUse) | Automatic gate |
| "Extract learnings on session end" | Hook (SessionEnd) | Automatic trigger |
| "Debug hooks step by step" | Skill | Manual sequence |
| "Always pass IDs explicitly" | Rule | Heuristic |
Step 5: Apply Signal Thresholds
| Occurrences | Action |
|---|---|
| 1 | Note but skip (unless critical failure) |
| 2 | Consider - present to user |
| 3+ | Strong signal - recommend creation |
| 4+ | Definitely create |
Step 6: Propose Artifacts
Present each proposal in this format:
---
## Pattern: [Generalized Name]
**Signal:** [N] sessions ([list session IDs])
**Category:** [debugging / reliability / workflow / etc.]
**Artifact Type:** Rule / Skill / Agent Update
**Rationale:** [Why this artifact type, why worth creating]
**Draft Content:**
\`\`\`markdown
[Actual content that would be written to file]
\`\`\`
**File:** `.claude/rules/[name].md` or `.claude/skills/[name]/SKILL.md`
---
Use AskUserQuestion to get approval for each artifact (or batch approval).
Step 7: Create Approved Artifacts
For Rules:
# Write to rules directory
cat > $CLAUDE_PROJECT_DIR/.claude/rules/<name>.md << 'EOF'
# Rule Name
[Context: why this rule exists, based on N sessions]
## Pattern
[The reusable principle]
## DO
- [Concrete action]
## DON'T
- [Anti-pattern]
## Source Sessions
- [session-id-1]: [what happened]
- [session-id-2]: [what happened]
EOF
For Skills:
Create .claude/skills/<name>/SKILL.md with:
- Frontmatter (name, description, allowed-tools)
- When to Use
- Step-by-step instructions (executable)
- Examples from the learnings
Add triggers to skill-rules.json if appropriate.
For Hooks:
Create shell wrapper + TypeScript handler:
# Shell wrapper
cat > $CLAUDE_PROJECT_DIR/.claude/hooks/<name>.sh << 'EOF'
#!/bin/bash
set -e
cd "$CLAUDE_PROJECT_DIR/.claude/hooks"
cat | node dist/<name>.mjs
EOF
chmod +x $CLAUDE_PROJECT_DIR/.claude/hooks/<name>.sh
Then create src/<name>.ts, build with esbuild, and register in settings.json:
{
"hooks": {
"EventName": [{
"hooks": [{
"type": "command",
"command": "$CLAUDE_PROJECT_DIR/.claude/hooks/<name>.sh"
}]
}]
}
}
For Agent Updates:
Edit existing agent in .claude/agents/<name>.md to add the learned capability.
Step 8: Summary Report
## Compounding Complete
**Learnings Analyzed:** [N] sessions
**Patterns Found:** [M]
**Artifacts Created:** [K]
### Created:
- Rule: `explicit-identity.md` - Pass IDs explicitly across boundaries
- Skill: `debug-hooks` - Hook debugging workflow
### Skipped (insufficient signal):
- "Pattern X" (1 occurrence)
**Your setup is now permanently improved.**
Quality Checks
Before creating any artifact:
- Is it general enough? Would it apply in other projects?
- Is it specific enough? Does it give concrete guidance?
- Does it already exist? Check
.claude/rules/and.claude/skills/first - Is it the right type? Sequences → skills, heuristics → rules
Files Reference
- Learnings:
.claude/cache/learnings/*.md - Skills:
.claude/skills/<name>/SKILL.md - Rules:
.claude/rules/<name>.md - Hooks:
.claude/hooks/<name>.sh+src/<name>.ts+dist/<name>.mjs - Agents:
.claude/agents/<name>.md - Skill triggers:
.claude/skills/skill-rules.json - Hook registration:
.claude/settings.json→hookssection
Source
git clone https://github.com/parcadei/Continuous-Claude-v3/blob/main/.claude/skills/compound-learnings/SKILL.mdView on GitHub Overview
Compound Learnings converts ephemeral session insights into permanent capabilities like skills, rules, and agents. It guides you through gathering the latest learnings, extracting patterns, consolidating them, and proposing actionable artifacts that reinforce improvements.
How This Skill Works
Starting from recent learnings, it reads the most relevant files, extracts patterns, takeaways, and success or anti patterns, builds a frequency map, and classifies each pattern as a Rule, Skill, or Agent Update. It applies signal thresholds to decide what to propose and prompts for approval via AskUserQuestion before creation.
When to Use It
- What should I learn from recent sessions?
- Improve my setup based on recent work
- Turn learnings into skills/rules
- What patterns should become permanent?
- Compound my learnings
Quick Start
- Step 1: Gather Learnings from the most recent session files in $CLAUDE_PROJECT_DIR/.claude/cache/learnings.
- Step 2: Extract patterns, takeaways, and success or anti patterns; build a frequency table and consolidate similar patterns.
- Step 3: Propose artifacts (Rule, Skill, or Agent Update) and use AskUserQuestion to obtain approval before creation.
Best Practices
- Focus on generalizable patterns rather than isolated tips.
- Consolidate similar patterns into a single generalized rule or skill.
- Use the frequency table to surface high-signal artifacts.
- Prefer artifact types that automate or guide workflows (Skill/Hook) over ad hoc rules.
- Always use AskUserQuestion to secure explicit approval before creating artifacts.
Example Use Cases
- Pattern: Observe outputs before editing code; Artifact: Create a Rule to always verify outputs before edits.
- Pattern: Always pass IDs explicitly; Artifact: Add a Rule enforcing explicit ID passing in all workflows.
- Pattern: Extract learnings on session end; Artifact: Create a Hook that auto extracts learnings at session termination.
- Pattern: Run linting before commit; Artifact: Implement a Hook (PreToolUse) that runs linting automatically.
- Pattern: Consolidate common setup steps into a Skill; Artifact: Develop a Skill that encapsulates repeated session setup tasks.