Self Improving Agent

基于本能的持续学习系统。通过置信度评分捕获原子学习（本能），支持项目范围与全局范围，并将本能发展为技能/命令/代理。在以下情况下使用：(1) 命令失败，(2) 用户纠正您，(3) 发现模式，(4) 需要回顾或发展学到的行为。支持 v1（基于 markdown）和 v2（基于 instinct）模式。

## 概述（中文）

基于本能的持续学习系统。通过置信度评分捕获原子学习（本能），支持项目范围与全局范围，并将本能发展为技能/命令/代理。在以下情况下使用：(1) 命令失败，(2) 用户纠正您，(3) 发现模式，(4) 需要回顾或发展学到的行为。支持 v1（基于 markdown）和 v2（基于 instinct）模式。

## 原文

# Self-Improving Agent Skill

An advanced learning system that turns Claude Code sessions into reusable knowledge through atomic "instincts" - small learned behaviors with confidence scoring and project scope isolation.

**v2.1** adds **project-scoped instincts** — React patterns stay in your React project, Python conventions stay in your Python project, and universal patterns are shared globally.

## Quick Reference

| Situation | Action |
|-----------|--------|
| Command/operation fails | Log instinct or v1 learning |
| User corrects you | Create instinct with `correction` trigger |
| Discovering patterns | Log instinct with confidence score |
| Review learned behaviors | `/instinct-status` |
| Evolve instincts to skills | `/evolve` |
| Promote project → global | `/promote` |
| Setup observation hooks | Enable PreToolUse/PostToolUse hooks |

## Two Learning Modes

### Mode 1: Instinct-Based (v2) - RECOMMENDED

Atomic, confidence-weighted behaviors with project isolation:

```yaml
---
id: prefer-functional-style
trigger: "when writing new functions"
confidence: 0.7
domain: "code-style"
scope: project
project_id: "a1b2c3d4e5f6"
---

# Prefer Functional Style

## Action
Use functional patterns over classes when appropriate.

## Evidence
- Observed 5 instances of functional pattern preference
- User corrected class-based approach on 2025-01-15
```

### Mode 2: Markdown-Based (v1) - LEGACY

Traditional learning entries for complex, narrative learnings:

```markdown
## [LRN-YYYYMMDD-XXX] category
**Priority**: high | **Status**: pending | **Area**: backend

### Summary
Detailed description of what was learned

### Details
Full context and explanation
```

Use v2 (instincts) for behavioral patterns, v1 (markdown) for complex incident analysis.

---

## Instinct-Based Learning (v2)

### The Instinct Model

An instinct is a small, atomic learned behavior:

**Properties:**
- **Atomic** — one trigger, one action
- **Confidence-weighted** — 0.3 = tentative, 0.9 = near certain
- **Domain-tagged** — code-style, testing, git, debugging, workflow, security, etc.
- **Evidence-backed** — tracks what observations created it
- **Scope-aware** — `project` (default) or `global`

### Confidence Scoring

| 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

### Scope Decision Guide

| Pattern Type | Scope | Examples |
|-------------|-------|---------|
| Language/framework conventions | **project** | "Use React hooks", "Follow Django REST patterns" |
| File structure preferences | **project** | "Tests in `__tests__`/", "Components in src/components/" |
| Code style | **project** | "Use functional style", "Prefer dataclasses" |
| Security practices | **global** | "Validate user input", "Sanitize SQL" |
| General best practices | **global** | "Write tests first", "Always handle errors" |
| Tool workflow preferences | **global** | "Grep before Edit", "Read before Write" |
| Git practices | **global** | "Conventional commits", "Small focused commits" |

### Project Detection

The system automatically detects your current project:

1. **`CLAUDE_PROJECT_DIR` env var** (highest priority)
2. **`git remote get-url origin`** — hashed to create a portable project ID
3. **`git rev-parse --show-toplevel`** — fallback using repo path
4. **Global fallback** — if no project detected, instincts go to global scope

Each project gets a 12-character hash ID (e.g., `a1b2c3d4e5f6`).

## v2 Commands

| Command | Description |
|---------|-------------|
| `/instinct-status` | Show all instincts (project-scoped + global) with confidence |
| `/evolve` | Cluster related instincts into skills/commands, suggest promotions |
| `/instinct-export` | Export instincts (filterable by scope/domain) |
| `/instinct-import <file>` | Import instincts with scope control |
| `/promote [id]` | Promote project instincts to global scope |
| `/projects` | List all known projects and their instinct counts |

### /instinct-status Example

```
Project: my-react-app (a1b2c3d4e5f6)
├─ prefer-functional-style.yaml (0.7) [project]
├─ use-react-hooks.yaml (0.9) [project]
└─ jest-testing-patterns.yaml (0.6) [project]

Global Instincts:
├─ always-validate-input.yaml (0.85) [global]
├─ grep-before-edit.yaml (0.6) [global]
└─ conventional-commits.yaml (0.75) [global]
```

### /evolve Workflow

Clusters related instincts and generates:
- **Skills** — domain-specific workflows
- **Commands** — slash commands for common tasks
- **Agents** — specialized sub-agents

```bash
/evolve
# Analyzes instincts and suggests:
# - "Create skill: react-testing-workflow.md"
# - "Create command: /test-component"
# - "Promote prefer-functional-style to global (seen in 3 projects)"
```

### /promote Workflow

Promote project-scoped instincts to global when proven across projects:

```bash
/promote prefer-explicit-errors
# Promotes the instinct from current project to global scope
```

**Auto-promotion criteria:**
- Same instinct ID in 2+ projects
- Average confidence >= 0.8

## File Structure (v2)

```
~/.claude/homunculus/
├── identity.json           # Your profile, technical level
├── projects.json           # Registry: project hash → name/path/remote
├── observations.jsonl      # Global observations (fallback)
├── instincts/
│   ├── personal/           # Global auto-learned instincts
│   └── inherited/          # Global imported instincts
├── evolved/
│   ├── agents/             # Global generated agents
│   ├── skills/             # Global generated skills
│   └── commands/           # Global generated commands
└── projects/
    ├── a1b2c3d4e5f6/       # Project hash
    │   ├── observations.jsonl
    │   ├── observations.archive/
    │   ├── instincts/
    │   │   ├── personal/   # Project-specific auto-learned
    │   │   └── inherited/  # Project-specific imported
    │   └── evolved/
    │       ├── skills/
    │       ├── commands/
    │       └── agents/
    └── f6e5d4c3b2a1/       # Another project
```

## Enabling Observation Hooks (v2)

Add to your `~/.claude/settings.json`:

```json
{
  "hooks": {
    "PreToolUse": [{
      "matcher": "*",
      "hooks": [{
        "type": "command",
        "command": "~/.claude/skills/self-improving-agent/hooks/observe.sh"
      }]
    }],
    "PostToolUse": [{
      "matcher": "*",
      "hooks": [{
        "type": "command",
        "command": "~/.claude/skills/self-improving-agent/hooks/observe.sh"
      }]
    }]
  }
}
```

**Why hooks?** Hooks fire **100% of the time**, deterministically. Skills fire ~50-80% based on Claude's judgment.

---

OpenClaw is the primary platform for this skill. It uses workspace-based prompt injection with automatic skill loading.

### Installation

**Via ClawdHub (recommended):**
```bash
clawdhub install self-improving-agent
```

**Manual:**
```bash
git clone https://github.com/peterskoett/self-improving-agent.git ~/.openclaw/skills/self-improving-agent
```

Remade for openclaw from original repo : https://github.com/pskoett/pskoett-ai-skills - https://github.com/pskoett/pskoett-ai-skills/tree/main/skills/self-improvement

### Workspace Structure

OpenClaw injects these files into every session:

```
~/.openclaw/workspace/
├── AGENTS.md          # Multi-agent workflows, delegation patterns
├── SOUL.md            # Behavioral guidelines, personality, principles
├── TOOLS.md           # Tool capabilities, integrati