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.
8.1
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AI & LLM
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Excellent skill documentation for Constitutional AI with comprehensive coverage of both theory and implementation. The description clearly explains the two-phase approach (SL + RLAIF) and when to use it. Task knowledge is strong with detailed code examples for self-critique/revision, RLAIF training, and reward modeling. Structure is logical with clear workflow separation and good use of references for advanced topics. Novelty is significant—implementing CAI from scratch requires understanding multi-phase training, self-critique mechanisms, and AI-generated preferences, which would be token-intensive for a CLI agent. Minor improvement areas: could benefit from more explicit error handling examples and clearer metrics for evaluating constitution effectiveness. The skill meaningfully reduces complexity for implementing this sophisticated safety alignment technique.
davila7
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