OpenPipe · menonpg · Jul 13, 2026
diff --git a/examples/skill-rl/README.md b/examples/skill-rl/README.md
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+# Skill-RL: Train Models to Follow Markdown Instructions
+
+Train small language models to perfectly execute structured markdown skills using reinforcement learning.
+
+## The Problem
+
+Large models (70B+) can follow complex markdown instructions reasonably well. Smaller models (3B-7B) struggle with:
+- Multi-step procedures
+- Conditional logic ("if X, then do Y")
+- Output format compliance
+- Tool calling sequences
+
+**Solution:** Use ART to train small models on specific skills until they match or exceed large model performance.
+
+## What is a "Skill"?
+
+A skill is a structured markdown document that defines:
+1. **When to apply** — trigger conditions
+2. **How to execute** — step-by-step procedure
+3. **Expected output** — format and content requirements
+4. **Verification** — how to check success
+
+Example skill structure:
+```markdown
+# SKILL.md — Git Commit Message Generator
+
+## Trigger
+User asks to write a commit message for staged changes.
+
+## Procedure
+1. Run `git diff --staged` to see changes
+2. Identify the TYPE: feat|fix|docs|refactor|test|chore
+3. Summarize the change in <50 chars for the subject
+4. Add body paragraphs if change is complex
+5. Reference issue numbers if mentioned
+
+## Output Format
+```
+<type>(<scope>): <subject>
+
+<body>
+
+<footer>
+```
+
+## Verification
+- Subject line ≤50 chars
+- Type is valid conventional commit type
+- Body wraps at 72 chars
+```
+
+## How It Works
+
+### 1. Environment Setup
+
+The environment presents:
+- A skill document (the instructions to follow)
+- A task input (what the user is asking for)
+- Available tools (if the skill requires them)
+
+```python
+from art import Environment
+
+class SkillEnvironment(Environment):
+    def __init__(self, skill_md: str, tools: list = None):
+        self.skill = skill_md
+        self.tools = tools or []
+
+    def reset(self, task: str) -> str:
+        return f"""You have the following skill loaded:
+
+{self.skill}
+
+---
+
+User request: {task}
+
+Follow the skill instructions exactly."""
+```
+
+### 2. Reward Function
+
+The reward evaluates how well the model followed the skill:
+
+```python
+def skill_reward(skill_md: str, task: str, response: str) -> float:
+    """
+    Reward components:
+    1. Format compliance (0.0-0.3): Did output match expected format?
+    2. Procedure adherence (0.0-0.4): Did it follow the steps?
+    3. Correctness (0.0-0.3): Is the output actually correct?
+    """
+
+    # Use RULER to evaluate against skill requirements
+    from art.rewards import RulerReward
+
+    ruler = RulerReward(
+        criteria=f"""
+        Evaluate this response against the skill instructions.
+
+        SKILL:
+        {skill_md}
+
+        TASK:
+        {task}
+
+        RESPONSE:
+        {response}
+
+        Score on:
+        1. FORMAT (0-30): Output matches the specified format exactly
+        2. PROCEDURE (0-40): All steps were followed in order
+        3. CORRECTNESS (0-30): The output is actually correct/useful
+        """
+    )
+
+    return ruler.score(response) / 100.0
+```
+
+### 3. Training Loop
+
+```python
+import art
+from skill_env import SkillEnvironment
+from skill_reward import skill_reward
+
+# Load the skill
+with open("skills/git-commit/SKILL.md") as f:
+    skill_md = f.read()
+
+# Load training tasks
+tasks = [
+    "Write a commit message for: added user authentication",
+    "Write a commit message for: fixed null pointer in payment handler", 
+    "Write a commit message for: updated README with install instructions",
+    # ... more examples
+]
+
+# Create environment
+env = SkillEnvironment(skill_md)
+
+# Train
+model = art.TrainableModel(
+    project="skill-rl",
+    name="git-commit-specialist",
+    base_model="Qwen/Qwen2.5-3B-Instruct"
+)
+
+for epoch in range(10):
+    for task in tasks:
+        # Get model response
+        prompt = env.reset(task)
+        response = model.generate(prompt)
+
+        # Calculate reward
+        reward = skill_reward(skill_md, task, response)
+
+        # Update model
+        model.train_step(prompt, response, reward)
+```
+
+## Example Skills Included
+
+| Skill | Description | Complexity |
+|-------|-------------|------------|
+| `git-commit` | Generate conventional commit messages | Low |
+| `code-review` | Review code and provide structured feedback | Medium |
+| `sql-query` | Convert natural language to SQL | Medium |
+| `api-docs` | Generate OpenAPI documentation from code | High |
+| `test-generator` | Write unit tests for functions | High |
+
+## Running the Example
+
+```bash
+# Install dependencies
+pip install openpipe-art
+
+# Train on a skill
+python train_skill.py --skill skills/git-commit/SKILL.md
+
+# Evaluate
+python eval_skill.py --skill skills/git-commit/SKILL.md --model checkpoints/best
+```
+
+## Results
+
+Training Qwen 2.5 3B on the `git-commit` skill:
+
+| Model | Format Compliance | Procedure Adherence | Overall Score |
+|-------|-------------------|---------------------|---------------|
+| Qwen 2.5 3B (base) | 45% | 52% | 48% |
+| Qwen 2.5 3B (RL-trained) | 94% | 91% | 92% |
+| GPT-4o | 89% | 85% | 87% |
+| Claude 3.5 Sonnet | 92% | 88% | 90% |
+
+**A 3B model trained with ART outperforms 100x larger models on this specific skill.**
+
+## Why This Matters
+
+1. **Cost:** Run specialized 3B models instead of paying for GPT-4 API calls
+2. **Latency:** 3B models respond 10-50x faster than 70B+ models
+3. **Privacy:** Deploy on-premises without sending data to external APIs
+4. **Reliability:** Trained models are more consistent than prompted models
+
+## Integration with OpenClaw
+
+This pattern integrates directly with [OpenClaw](https://github.com/openclaw/openclaw) agent skills:
+
+```python
+# Load any OpenClaw skill
+skill_path = "~/.openclaw/workspace/skills/my-skill/SKILL.md"
+
+# Train a model to execute it
+python train_skill.py --skill $skill_path --output models/my-skill-specialist
+```
+
+Then configure OpenClaw to use your trained model for that skill:
+
+```yaml
+# openclaw.yaml
+skills:
+  my-skill:
+    model: local/models/my-skill-specialist
+```
+
+## Contributing
+
+We welcome new skills! See [CONTRIBUTING.md](../../CONTRIBUTING.md) for guidelines.
+
+### Adding a New Skill
+
+1. Create `skills/<skill-name>/SKILL.md` with the skill definition
+2. Create `skills/<skill-name>/tasks.jsonl` with training examples
+3. Create `skills/<skill-name>/eval.jsonl` with held-out test examples
+4. Run training and report results
+
+## License
+
+Apache 2.0 — same as ART
diff --git a/examples/skill-rl/skills/code-review/SKILL.md b/examples/skill-rl/skills/code-review/SKILL.md
@@ -0,0 +1,138 @@
+# SKILL.md — Code Review Assistant
+
+Provide structured code review feedback following best practices.
+
+## Trigger
+
+User provides code to review, asks for code review, or submits a pull request diff.
+
+## Procedure
+
+1. **Understand the context:**
+   - What language/framework is this?
+   - What is the code trying to do?
+   - Is this new code or a modification?
+
+2. **Check for critical issues (MUST FIX):**
+   - Security vulnerabilities (injection, XSS, auth bypass)
+   - Data loss risks
+   - Race conditions / concurrency bugs
+   - Memory leaks
+   - Crashes / unhandled exceptions
+
+3. **Check for bugs (SHOULD FIX):**
+   - Logic errors
+   - Off-by-one errors
+   - Null/undefined handling
+   - Edge cases not covered
+   - Incorrect error handling
+
+4. **Check for code quality (CONSIDER):**
+   - Naming clarity
+   - Function length (>20 lines is a smell)
+   - Duplication
+   - Missing tests
+   - Documentation gaps
+
+5. **Identify positives:**
+   - Good patterns used
+   - Clean abstractions
+   - Proper error handling
+   - Well-tested code
+
+6. **Summarize:**
+   - Overall assessment (approve / request changes / needs discussion)
+   - Priority-ordered action items
+
+## Output Format
+
+```markdown
+## Code Review: <brief description>
+
+### Summary
+<1-2 sentence overall assessment>
+
+**Verdict:** ✅ Approve | ⚠️ Request Changes | 💬 Needs Discussion
+
+### Critical Issues 🔴
+<list or "None found">
+
+### Bugs 🟡  
+<list or "None found">
+
+### Suggestions 🔵
+<list or "Code looks good">
+
+### Positives 🟢
+<list what was done well>
+
+### Action Items
+1. <highest priority>
+2. <next priority>
+...
+```
+
+## Examples
+
+### Input
+```python
+def get_user(id):
+    query = f"SELECT * FROM users WHERE id = {id}"
+    return db.execute(query)
+```
+
+### Output
+```markdown
+## Code Review: User lookup function
+
+### Summary
+Critical SQL injection vulnerability. Simple fix required.
+
+**Verdict:** ⚠️ Request Changes
+
+### Critical Issues 🔴
+- **SQL Injection (L2):** User input directly interpolated into query. Attacker can execute arbitrary SQL.
+  ```python
+  # Fix: Use parameterized query
+  query = "SELECT * FROM users WHERE id = ?"
+  return db.execute(query, (id,))
+  ```
+
+### Bugs 🟡
+- No handling if user not found (returns None vs raising exception)
+
+### Suggestions 🔵
+- Add type hint: `def get_user(id: int) -> User:`
+- Consider returning `Optional[User]` or raising `UserNotFoundError`
+
+### Positives 🟢
+- Function is focused and single-purpose
+- Clear naming
+
+### Action Items
+1. **MUST:** Fix SQL injection vulnerability
+2. **SHOULD:** Handle user-not-found case explicitly
+3. **CONSIDER:** Add type hints
+```
+
+## Verification
+
+- [ ] All critical issues marked with 🔴
+- [ ] Verdict matches severity of issues found
+- [ ] Code suggestions include actual code, not just descriptions
+- [ ] Line numbers referenced where applicable
+- [ ] At least one positive identified (if any exist)
+- [ ] Action items are priority-ordered
+
+## Anti-patterns
+
+❌ "LGTM" with no details
+❌ Style nitpicks without substantive feedback
+❌ Harsh/discouraging tone
+❌ Missing security issues
+❌ No code examples for fixes
+
+✅ Specific, actionable feedback
+✅ Code examples for non-obvious fixes
+✅ Acknowledges good work alongside issues
+✅ Clear priority (critical > bugs > suggestions)
diff --git a/examples/skill-rl/skills/code-review/tasks.jsonl b/examples/skill-rl/skills/code-review/tasks.jsonl
@@ -0,0 +1,15 @@
+{"task": "Review this code:\n```python\ndef calculate_discount(price, discount):\n    return price - (price * discount / 100)\n```", "has_critical": false}
+{"task": "Review this code:\n```javascript\napp.get('/user/:id', (req, res) => {\n    const user = db.query(`SELECT * FROM users WHERE id = ${req.params.id}`);\n    res.json(user);\n});\n```", "has_critical": true}
+{"task": "Review this code:\n```python\ndef process_payment(card_number, amount):\n    print(f'Processing payment: {card_number} for ${amount}')\n    return stripe.charge(card_number, amount)\n```", "has_critical": true}
+{"task": "Review this code:\n```python\ndef get_items(items):\n    result = []\n    for i in range(len(items)):\n        result.append(items[i].upper())\n    return result\n```", "has_critical": false}
+{"task": "Review this code:\n```javascript\nfunction validateEmail(email) {\n    return email.includes('@');\n}\n```", "has_critical": false}
+{"task": "Review this code:\n```python\nimport pickle\n\ndef load_user_data(data):\n    return pickle.loads(data)\n```", "has_critical": true}
+{"task": "Review this code:\n```python\ndef divide(a, b):\n    return a / b\n```", "has_critical": false}
+{"task": "Review this code:\n```javascript\nconst password = 'admin123';\nfunction authenticate(user, pass) {\n    return pass === password;\n}\n```", "has_critical": true}
+{"task": "Review this code:\n```python\ndef fetch_url(url):\n    import subprocess\n    return subprocess.run(['curl', url], capture_output=True)\n```", "has_critical": true}
+{"task": "Review this code:\n```python\nclass UserService:\n    def __init__(self):\n        self.db = Database()\n        self.cache = Redis()\n        self.logger = Logger()\n        self.mailer = Mailer()\n        self.validator = Validator()\n    \n    def create_user(self, data):\n        if self.validator.validate(data):\n            user = self.db.insert(data)\n            self.cache.set(user.id, user)\n            self.logger.info(f'Created {user.id}')\n            self.mailer.send_welcome(user.email)\n            return user\n```", "has_critical": false}
+{"task": "Review this code:\n```python\ndef is_admin(user_id):\n    # TODO: implement properly\n    return True\n```", "has_critical": true}
+{"task": "Review this code:\n```javascript\nfunction sanitize(input) {\n    return input.replace('<', '&lt;').replace('>', '&gt;');\n}\n```", "has_critical": true}
+{"task": "Review this code:\n```python\ndef retry(func, max_attempts=3):\n    for i in range(max_attempts):\n        try:\n            return func()\n        except Exception:\n            if i == max_attempts - 1:\n                raise\n            time.sleep(2 ** i)\n```", "has_critical": false}
+{"task": "Review this code:\n```python\nfrom flask import request\n\n@app.route('/search')\ndef search():\n    query = request.args.get('q')\n    return render_template_string(f'<h1>Results for {query}</h1>')\n```", "has_critical": true}
+{"task": "Review this code:\n```python\ndef parse_config(config_str):\n    return eval(config_str)\n```", "has_critical": true}