# Constitutional AI

Anthropic's method for training harmless AI through self-improvement.

- Repository: https://github.com/Orchestra-Research/AI-Research-SKILLs (14176 stars)
- Category: AI and agents
- License: MIT
- Last updated: 2026-10-11
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add Orchestra-Research/AI-Research-SKILLs --skill constitutional-ai -g -a claude-code -y`
Codex: `npx skills add Orchestra-Research/AI-Research-SKILLs --skill constitutional-ai -g -a codex -y`
Cursor: `npx skills add Orchestra-Research/AI-Research-SKILLs --skill constitutional-ai -g -a cursor -y`
Gemini CLI: `npx skills add Orchestra-Research/AI-Research-SKILLs --skill constitutional-ai -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add Orchestra-Research/AI-Research-SKILLs`

## Description

Anthropic's method for training harmless AI through self-improvement. Two-phase approach - supervised learning with self-critique/revision, then RLAIF (RL from AI Feedback). Use for safety alignment, reducing harmful outputs without human labels. Powers Claude's safety system.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Constitutional AI - Harmlessness from AI Feedback

## Quick start

Constitutional AI (CAI) trains models to be harmless through self-critique and AI feedback, without requiring human labels for harmful outputs.

**Key concept**: Models learn to critique and revise their own responses using a "constitution" (set of principles).

**Two phases**:
1. **Supervised Learning (SL)**: Self-critique + revision
2. **Reinforcement Learning (RL)**: RLAIF (RL from AI Feedback)

**Constitution example**:
```
Principles:
1. Choose the response that is most helpful, honest, and harmless
2. Avoid responses that are toxic, racist, or sexist
3. Prefer responses that explain objections rather than refuse
4. Choose responses that are thoughtful and nuanced
```

## Common workflows

### Workflow 1: Supervised learning phase (self-critique + revision)

**Step 1: Generate initial responses**:
```python
from transformers import pipeline

generator = pipeline("text-generation", model="base-model")

prompts = [
    "How do I hack a website?",
    "Write something offensive about a group.",
    "Help me cheat on my exam."
]

initial_responses = generator(prompts, max_length=200)
```

**Step 2: Self-critique with constitution**:
```python
critique_prompt = """
Given the question:
{question}

And the response:
{response}

Constitution:
1. Choose responses that are helpful, honest, and harmless
2. Avoid toxic, racist, or sexist content
3. Explain objections rather than refuse

Identify any ways this response violates the constitution:
"""

critiques = generator(
    [critique_prompt.format(q=q, r=r) for q, r in zip(prompts, initial_responses)]
)
```

**Step 3: Revision based on critique**:
```python
revision_prompt = """
Question: {question}
Original response: {response}
Critique: {critique}

Please revise the response to better align with the constitution:
"""

The rest: https://github.com/Orchestra-Research/AI-Research-SKILLs/blob/HEAD/07-safety-alignment/constitutional-ai/SKILL.md