continuous-learning-v2
Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents.
Best use case
continuous-learning-v2 is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents.
Teams using continuous-learning-v2 should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/continuous-learning-v2/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How continuous-learning-v2 Compares
| Feature / Agent | continuous-learning-v2 | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Continuous Learning v2 - Instinct-Based Architecture
An advanced learning system that turns your Claude Code sessions into reusable knowledge through atomic "instincts" - small learned behaviors with confidence scoring.
## What's New in v2
| Feature | v1 | v2 |
|---------|----|----|
| Observation | Stop hook (session end) | PreToolUse/PostToolUse (100% reliable) |
| Analysis | Main context | Background agent (Haiku) |
| Granularity | Full skills | Atomic "instincts" |
| Confidence | None | 0.3-0.9 weighted |
| Evolution | Direct to skill | Instincts → cluster → skill/command/agent |
| Sharing | None | Export/import instincts |
## The Instinct Model
An instinct is a small learned behavior:
```yaml
---
id: prefer-functional-style
trigger: "when writing new functions"
confidence: 0.7
domain: "code-style"
source: "session-observation"
---
# Prefer Functional Style
## Action
Use functional patterns over classes when appropriate.
## Evidence
- Observed 5 instances of functional pattern preference
- User corrected class-based approach to functional on 2025-01-15
```
**Properties:**
- **Atomic** — one trigger, one action
- **Confidence-weighted** — 0.3 = tentative, 0.9 = near certain
- **Domain-tagged** — code-style, testing, git, debugging, workflow, etc.
- **Evidence-backed** — tracks what observations created it
## How It Works
```
Session Activity
│
│ Hooks capture prompts + tool use (100% reliable)
▼
┌─────────────────────────────────────────┐
│ observations.jsonl │
│ (prompts, tool calls, outcomes) │
└─────────────────────────────────────────┘
│
│ Observer agent reads (background, Haiku)
▼
┌─────────────────────────────────────────┐
│ PATTERN DETECTION │
│ • User corrections → instinct │
│ • Error resolutions → instinct │
│ • Repeated workflows → instinct │
└─────────────────────────────────────────┘
│
│ Creates/updates
▼
┌─────────────────────────────────────────┐
│ instincts/personal/ │
│ • prefer-functional.md (0.7) │
│ • always-test-first.md (0.9) │
│ • use-zod-validation.md (0.6) │
└─────────────────────────────────────────┘
│
│ /evolve clusters
▼
┌─────────────────────────────────────────┐
│ evolved/ │
│ • commands/new-feature.md │
│ • skills/testing-workflow.md │
│ • agents/refactor-specialist.md │
└─────────────────────────────────────────┘
```
## Quick Start
### 1. Enable Observation Hooks
Add to your `~/.claude/settings.json`:
```json
{
"hooks": {
"PreToolUse": [{
"matcher": "*",
"hooks": [{
"type": "command",
"command": "~/.claude/skills/continuous-learning-v2/hooks/observe.sh pre"
}]
}],
"PostToolUse": [{
"matcher": "*",
"hooks": [{
"type": "command",
"command": "~/.claude/skills/continuous-learning-v2/hooks/observe.sh post"
}]
}]
}
}
```
### 2. Initialize Directory Structure
```bash
mkdir -p ~/.claude/homunculus/{instincts/{personal,inherited},evolved/{agents,skills,commands}}
touch ~/.claude/homunculus/observations.jsonl
```
### 3. Run the Observer Agent (Optional)
The observer can run in the background analyzing observations:
```bash
# Start background observer
~/.claude/skills/continuous-learning-v2/agents/start-observer.sh
```
## Commands
| Command | Description |
|---------|-------------|
| `/instinct-status` | Show all learned instincts with confidence |
| `/evolve` | Cluster related instincts into skills/commands |
| `/instinct-export` | Export instincts for sharing |
| `/instinct-import <file>` | Import instincts from others |
## Configuration
Edit `config.json`:
```json
{
"version": "2.0",
"observation": {
"enabled": true,
"store_path": "~/.claude/homunculus/observations.jsonl",
"max_file_size_mb": 10,
"archive_after_days": 7
},
"instincts": {
"personal_path": "~/.claude/homunculus/instincts/personal/",
"inherited_path": "~/.claude/homunculus/instincts/inherited/",
"min_confidence": 0.3,
"auto_approve_threshold": 0.7,
"confidence_decay_rate": 0.05
},
"observer": {
"enabled": true,
"model": "haiku",
"run_interval_minutes": 5,
"patterns_to_detect": [
"user_corrections",
"error_resolutions",
"repeated_workflows",
"tool_preferences"
]
},
"evolution": {
"cluster_threshold": 3,
"evolved_path": "~/.claude/homunculus/evolved/"
}
}
```
## File Structure
```
~/.claude/homunculus/
├── identity.json # Your profile, technical level
├── observations.jsonl # Current session observations
├── observations.archive/ # Processed observations
├── instincts/
│ ├── personal/ # Auto-learned instincts
│ └── inherited/ # Imported from others
└── evolved/
├── agents/ # Generated specialist agents
├── skills/ # Generated skills
└── commands/ # Generated commands
```
## Integration with Skill Creator
When you use the [Skill Creator GitHub App](https://skill-creator.app), it now generates **both**:
- Traditional SKILL.md files (for backward compatibility)
- Instinct collections (for v2 learning system)
Instincts from repo analysis have `source: "repo-analysis"` and include the source repository URL.
## Confidence Scoring
Confidence evolves over time:
| Score | Meaning | Behavior |
|-------|---------|----------|
| 0.3 | Tentative | Suggested but not enforced |
| 0.5 | Moderate | Applied when relevant |
| 0.7 | Strong | Auto-approved for application |
| 0.9 | Near-certain | Core behavior |
**Confidence increases** when:
- Pattern is repeatedly observed
- User doesn't correct the suggested behavior
- Similar instincts from other sources agree
**Confidence decreases** when:
- User explicitly corrects the behavior
- Pattern isn't observed for extended periods
- Contradicting evidence appears
## Why Hooks vs Skills for Observation?
> "v1 relied on skills to observe. Skills are probabilistic—they fire ~50-80% of the time based on Claude's judgment."
Hooks fire **100% of the time**, deterministically. This means:
- Every tool call is observed
- No patterns are missed
- Learning is comprehensive
## Backward Compatibility
v2 is fully compatible with v1:
- Existing `~/.claude/skills/learned/` skills still work
- Stop hook still runs (but now also feeds into v2)
- Gradual migration path: run both in parallel
## Privacy
- Observations stay **local** on your machine
- Only **instincts** (patterns) can be exported
- No actual code or conversation content is shared
- You control what gets exported
## Agent Memory Integration
continuous-learning-v2의 instinct 시스템은 에이전트의 Self-Evolution Protocol과 상호보완적으로 동작한다.
### 관계도
````
Continuous Learning v2 (세션 관찰 기반)
└─ observations.jsonl → instincts/personal/ → evolved/
↕ 상호 참조
Agent Self-Evolution (작업 완료 기반)
└─ 에이전트 작업 결과 → ~/.claude/agent-memory/{agent-name}/
````
### 차이점
| 차원 | Continuous Learning v2 | Agent Self-Evolution |
|------|----------------------|---------------------|
| 트리거 | 세션 관찰 (hooks) | 에이전트 작업 완료 |
| 저장소 | `~/.claude/homunculus/instincts/` | `~/.claude/agent-memory/` |
| 형태 | 원자적 instinct (trigger + action) | Learnings 리스트 (발견/개선) |
| 대상 | 전체 (범용) | 개별 에이전트 |
| 자동화 | Hook → Observer → Instinct (자동) | 에이전트 작업 완료 후 자체 기록 |
### 통합 사용 시나리오
1. **세션 중**: continuous-learning-v2 hooks가 관찰 데이터 수집
2. **에이전트 작업 후**: 에이전트가 Self-Evolution으로 자체 memory 업데이트
3. **세션 종료**: `/session-wrap`이 양쪽 데이터를 종합하여 정리
4. **다음 세션 시작**: `/sync`로 프로젝트 문서 동기화
## Related
- [Skill Creator](https://skill-creator.app) - Generate instincts from repo history
- [Homunculus](https://github.com/humanplane/homunculus) - Inspiration for v2 architecture
- [The Longform Guide](https://x.com/affaanmustafa/status/2014040193557471352) - Continuous learning section
---
*Instinct-based learning: teaching Claude your patterns, one observation at a time.*Related Skills
verify-implementation
프로젝트의 모든 verify 스킬을 실행하여 통합 패턴 검증 보고서를 생성합니다. 기능 구현 후, PR 전, 코드 리뷰 시 사용.
verification-engine
통합 검증 엔진 - 서브에이전트 기반 fresh-context 검증 루프 (v6)
using-superpowers
Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions
team-orchestrator
Agent Teams 오케스트레이션 엔진 - 팀 구성, 작업 분배, 의존성 관리, 결과 집계
strategic-compact
Suggests manual context compaction at logical intervals to preserve context through task phases rather than arbitrary auto-compaction.
skill-factory
Analyze session work and automatically convert reusable patterns into Claude Code skills. Use when: "세션을 스킬로", "스킬 만들어", "이거 스킬로", "skill factory", "이 작업 자동화해", "스킬 추출", "make this a skill", "extract skill", "convert to skill", "스킬 팩토리", "자동 스킬 생성". Differs from skill-creator (archived) and manage-skills (drift detection): this skill actively analyzes sessions, checks for duplicates, and creates skills via Agent Teams.
session-wrap
세션 종료 전 자동 정리 스킬. 4개 병렬 subagent가 문서 업데이트, 반복 패턴, 학습 포인트, 후속 작업을 동시 탐지하고, 1개 검증 subagent가 중복 제거 후 사용자에게 선택지를 제시한다. 트리거: /session-wrap, 세션 마무리, 세션 정리, 작업 마무리
security-pipeline
보안 파이프라인 - CWE Top 25 + STRIDE 자동 검증
prompts-chat
스킬/프롬프트 탐색 및 검색 통합 스킬. 사용자가 스킬 설치, 프롬프트 검색, 프롬프트 개선을 요청할 때 활성화.
manage-skills
세션 변경사항을 분석하여 검증 스킬 누락을 탐지합니다. 기존 스킬을 동적으로 탐색하고, 새 스킬을 생성하거나 기존 스킬을 업데이트한 뒤 프로젝트 CLAUDE.md를 관리합니다.
frontend-code-review
Trigger when the user requests a review of frontend files (e.g., `.tsx`, `.ts`, `.js`). Support both pending-change reviews and focused file reviews while applying the checklist rules.
eval-harness
Formal evaluation framework for Claude Code sessions implementing eval-driven development (EDD) principles