MCPInstall

compound-learnings

Transform session learnings into permanent capabilities (skills, rules, agents). Use when asked to "improve setup", "learn from sessions", "compound learnings", or "what patterns should become skills".

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/parcadei/continuous-claude-v3 --skill compound-learnings
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads compound-learnings automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Compound 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 HeaderWhat to Extract
## Patterns or Reusable techniquesDirect candidates for rules
**Takeaway:** or **Actionable takeaway:**Decision heuristics
## What WorkedSuccess patterns
## What FailedAnti-patterns (invert to rules)
## Key DecisionsDesign 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:

PatternTypeWhy
"Run linting before commit"Hook (PreToolUse)Automatic gate
"Extract learnings on session end"Hook (SessionEnd)Automatic trigger
"Debug hooks step by step"SkillManual sequence
"Always pass IDs explicitly"RuleHeuristic

Step 5: Apply Signal Thresholds

OccurrencesAction
1Note but skip (unless critical failure)
2Consider - 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:

  1. Is it general enough? Would it apply in other projects?
  2. Is it specific enough? Does it give concrete guidance?
  3. Does it already exist? Check .claude/rules/ and .claude/skills/ first
  4. 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 → hooks section

FAQ

What does the compound-learnings skill do?

Transform session learnings into permanent capabilities (skills, rules, agents). Use when asked to "improve setup", "learn from sessions", "compound learnings", or "what patterns should become skills".

How do I install compound-learnings?

Run npx skills add https://github.com/parcadei/continuous-claude-v3 --skill compound-learnings in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/compound-learnings/ (personal) or .claude/skills/compound-learnings/ (project).

Which AI agents can use compound-learnings?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is compound-learnings safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains compound-learnings?

It is published by parcadei in parcadei/continuous-claude-v3. It has 505 recorded installs.

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