Claude Reflect - Self-Learning System

A two-stage system that helps Claude Code learn from user corrections.

How It Works

Stage 1: Capture (Automatic) Hooks detect correction patterns ("no, use X", "actually...", "use X not Y") and queue them to ~/.claude/learnings-queue.json.

Stage 2: Process (Manual) User runs /reflect to review and apply queued learnings to CLAUDE.md files.

Available Commands

Command	Purpose
/reflect	Process queued learnings with human review
/reflect --scan-history	Scan past sessions for missed learnings
/reflect --dry-run	Preview changes without applying
/reflect-skills	Discover skill candidates from repeating patterns
/skip-reflect	Discard all queued learnings
/view-queue	View pending learnings without processing

When to Remind Users

Remind users about /reflect when:

• They complete a feature or meaningful work unit
• They make corrections you should remember for future sessions
• They explicitly say "remember this" or similar
• Context is about to compact and queue has items

Correction Detection Patterns

High-confidence corrections:

• Tool rejections (user stops an action with guidance)
• "no, use X" / "don't use Y"
• "actually..." / "I meant..."
• "use X not Y" / "X instead of Y"
• "remember:" (explicit marker)

Learning Destinations

• ~/.claude/CLAUDE.md - Global learnings (model names, general patterns)
• ./CLAUDE.md - Project-specific learnings (conventions, tools, structure)
• ./CLAUDE.local.md - Personal learnings (machine-specific, gitignored)
• ./.claude/rules/*.md - Modular rules with optional path-scoping
• ~/.claude/rules/*.md - Global modular rules
• ~/.claude/projects/<project>/memory/*.md - Auto memory (low-confidence, exploratory)
• commands/*.md - Skill improvements (corrections during skill execution)

Example Interaction

User: no, use gpt-5.1 not gpt-5 for reasoning tasks
Claude: Got it,...