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constitutional-ai

Enforce constitution-driven self-critique and AI feedback loops for model safety.

Updated Apr 3, 2026
Search Tags:#constitutional-ai#self-critique#ai-safety#ai-governance#rlaif#safety-alignment
One-click install
npx skills add https://github.com/handsomelong922/my-codex-skills --skill constitutional-ai-handsomelong922
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: constitutional-ai
Source: https://github.com/handsomelong922/my-codex-skills/tree/main/skills/constitutional-ai
Command: npx skills add https://github.com/handsomelong922/my-codex-skills --skill constitutional-ai-handsomelong922

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires transformers, torch, trl.

What problem does it solve?

Constitutional AI enables models to be harmless through self-critique and AI feedback, reducing reliance on human labeling.

Core Features & Use Cases

  • Self-critique with a constitution: generate critiques and revisions to align outputs with defined principles.
  • RL from AI Feedback: scalable preference learning without human labeling for safety.
  • Chain-of-thought reasoning prompts: promote transparent evaluation and revision.
  • Reference-guided design: guidelines and examples to design constitutions and policies.

Quick Start

Run the two-phase constitutional workflow to align your model to harmlessness.

Frequently Asked Questions about constitutional-ai

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How does AI feedback and self-critique work for safety alignment?▼

AI feedback and self-critique work by enforcing a constitution-driven loop where models generate critiques and revisions of their own outputs, aligning behavior with defined principles without human labels.

How do I align model behavior without human labels using RLAIF?▼

You can align model behavior without human labels using RLAIF by running a two-phase constitutional workflow: supervised learning from self-critique revisions, followed by reinforcement learning from AI feedback.

Can I use transformers and torch to implement a constitution-driven feedback loop?▼

Yes, you can use transformers and torch to implement a constitution-driven feedback loop, leveraging the trl library to execute the supervised and reinforcement learning phases for scalable safety alignment.

What is the best way to design a constitution for AI governance?▼

The best way to design a constitution for AI governance is to use reference-guided guidelines and examples, defining core principles that guide transparent chain-of-thought evaluation and policy alignment workflows.

When do I need constitutional AI for harmlessness instead of human labeling?▼

You need constitutional AI for harmlessness when scaling safety alignment across model development pipelines, specifically to reduce reliance on human labeling for preference learning and policy revisions.

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