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.
6.4
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0
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AI & LLM
Category
Well-structured skill with comprehensive coverage of Constitutional AI's two-phase approach (supervised learning with self-critique and RLAIF). The description clearly explains the method and use cases. Task knowledge is excellent with detailed code examples for all three workflows (SL phase, RL phase, and chain-of-thought critique), troubleshooting guidance, and practical implementation details. Structure is clean with logical progression and appropriate references to external files for advanced topics. However, novelty is limited because this is primarily a wrapper around existing libraries (transformers, trl) that a capable CLI agent could already use. The skill synthesizes Constitutional AI methodology well but doesn't provide unique tooling or significantly reduce implementation complexity beyond what standard RLHF/RLAIF tutorials offer. Most valuable for teams specifically wanting to implement Anthropic's CAI approach systematically.
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