learner

name	learner
description	Extract hard-won principles from the current session and save as reusable learned skills.
argument-hint	[--from-session | --from-diff | <topic>]
allowed-tools	Read, Write, Edit, Bash, Glob, Grep, AskUserQuestion
disable-model-invocation	true

Learner — Extract Hard-Won Principles

Capture non-obvious, context-specific insights from your current work and save them as reusable skill files that Maestro can inject into future sessions.

Arguments

• --from-session — Analyze the current session for learnings (default)
• --from-diff — Analyze recent git diff for patterns
• <topic> — Extract learnings about a specific topic

Hard Rules

• Quality over quantity: One excellent principle beats ten mediocre ones.
• No snippets: Capture the why and when, not code blocks. If code is needed, it's a pattern, not a learning.
• Verify uniqueness: Check existing .claude/skills/learned/ before saving duplicates.

Quality Gates

Every extracted principle MUST pass ALL four gates:

Gate	Question	Fail Example
Non-Googleable	Would a developer find this in docs/Stack Overflow?	"Use async/await for promises"
Context-Specific	Is this specific to THIS project or domain?	"Always validate input" (too generic)
Actionable	Can someone act on this immediately?	"The system is complex" (observation, not action)
Hard-Won	Did this cost time/debugging to discover?	"TypeScript has interfaces" (trivial)

Workflow

Step 1: Gather Evidence

Based on the argument:

--from-session (default):

1. Review conversation history for: corrections, debugging sessions, unexpected behavior, workarounds
2. Look for moments where assumptions were wrong

--from-diff:

1. Run git diff HEAD~5..HEAD (or appropriate range)
2. Identify non-obvious patterns in the changes
3. Look for: error handling patterns, API usage that wasn't obvious, config gotchas

<topic>:

1. Search codebase for topic-related files
2. Identify conventions and patterns
3. Note gotchas and edge cases

Step 2: Extract Principles

For each candidate learning:

1. Apply all four quality gates
2. If any gate fails, discard or refine
3. Format as a principle with trigger conditions

Step 3: Present for Approval

Show extracted principles to user:

AskUserQuestion(
  questions: [{
    question: "Save these learnings?",
    header: "Learnings",
    options: [
      { label: "Save all", description: "Save all extracted principles" },
      { label: "Select individually", description: "Choose which to save" },
      { label: "Discard", description: "Don't save any" }
    ],
    multiSelect: false
  }]
)

Step 4: Save

For each approved principle, create a skill file:

File: .claude/skills/learned/{slug}.md

---
name: {slug}
description: {one-line summary}
triggers:
  - {keyword1}
  - {keyword2}
priority: 200
---

# {Title}

## When This Applies
{Trigger conditions — when should this knowledge be surfaced?}

## The Principle
{The actual learning — what to do and why}

## Why This Matters
{What goes wrong without this knowledge}

## Evidence
{Where this was discovered — file paths, error messages, debugging session}

Slug derivation: Lowercase, hyphenated, max 5 words from the principle title.

Step 5: Confirm

Report what was saved:

• Number of principles extracted vs. saved
• File paths created
• Trigger keywords that will surface these in future sessions

Storage

• Location: .claude/skills/learned/*.md
• Discovery: Picked up automatically by Maestro's skill registry (session-start.sh parses .claude/skills/*/SKILL.md)
• Priority: 200 (lower than project skills at 100, so they supplement rather than override)

Anti-Patterns

Don't	Do Instead
Save code snippets	Save the principle behind the pattern
Save generic advice	Save project-specific insights
Save obvious things	Save things that took debugging to learn
Save without triggers	Always include trigger keywords for discoverability