continuous-learning-v2

name	continuous-learning-v2
description	Instinct-based learning system that observes development patterns via hooks and builds a knowledge base of reusable instincts with confidence scoring. Instincts evolve from observations into skills, commands, and agents.
license	MIT
compatibility	Claude Code 2.1+
metadata	{"author":"peopleforrester","version":"2.0.0","tags":["learning","automation","hooks","patterns"]}

Continuous Learning v2: Instinct-Based System

Learn from development sessions automatically using hook-based observation and confidence-scored instincts.

Why v2?

v1 used skills for learning (probabilistic activation, 50-80% reliability). v2 uses hooks (deterministic, 100% reliability) with structured instincts.

Core Concepts

Instincts

Atomic units of learned behavior with confidence scoring:

---
id: prefer-const-assertions
trigger: "when defining constant arrays or objects in TypeScript"
confidence: 0.7
domain: "code-style"
source: "session-observation"
---
# Use `as const` for constant definitions

TypeScript `as const` assertions provide literal types and readonly guarantees.

## Pattern
```typescript
const ROLES = ['admin', 'user', 'guest'] as const;
type Role = typeof ROLES[number];

Evidence

• Applied in 3 sessions
• Approved by reviewer each time
• Matches TypeScript best practices

### Confidence Levels

| Score | Level | Behavior |
|-------|-------|----------|
| 0.3 | Tentative | Suggested, not enforced |
| 0.5 | Moderate | Applied when context matches |
| 0.7 | Strong | Auto-applied, can be overridden |
| 0.9 | Near-certain | Core behavior, always applied |

### Confidence Evolution
- New observation: starts at 0.3
- Repeated application without correction: +0.1 per session
- User correction/rejection: -0.2
- Maximum: 0.9 (never fully automatic)

## Observation Hooks

### PreToolUse Observer
Before tool execution, check if any instincts apply:
```json
{
  "matcher": "tool == \"Write\" || tool == \"Edit\"",
  "type": "message",
  "message": "Check instincts for applicable patterns before writing code."
}

PostToolUse Observer

After tool execution, look for learnable patterns:

{
  "matcher": "tool == \"Edit\" && result.success == true",
  "type": "command",
  "command": "FILE=$(jq -r '.tool_input.file_path') && echo \"Pattern observed: successful edit to $FILE\"",
  "async": true
}

Instinct Lifecycle

Observation → Instinct (0.3) → Strengthened (0.5-0.7) → Evolved (0.9)
                    ↓                                        ↓
              Weakened/Removed                    Promoted to Skill/Rule

Commands

Command	Purpose
/learn	Extract patterns from current session
/checkpoint	Save state including instinct observations

Storage

Instincts stored in ~/.claude/instincts/ as markdown files:

~/.claude/instincts/
  prefer-const-assertions.md
  use-errgroup-for-goroutines.md
  validate-inputs-with-zod.md

Evolution Path

When instincts cluster around a domain, they can be promoted:

• 3+ related instincts → candidate for a Skill
• 5+ high-confidence instincts → candidate for a Rule
• Domain-specific cluster → candidate for an Agent prompt

Best Practices

• Review instincts periodically (monthly)
• Export instincts when switching projects to preserve learning
• Share instincts with team members for consistency
• Prune instincts that haven't been triggered in 30+ days