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Found 6 Skills
Launch an intelligent sub-agent with automatic model selection based on task complexity, specialized agent matching, Zero-shot CoT reasoning, and mandatory self-critique verification
Launch an intelligent sub-agent with automatic model selection based on task complexity, specialized agent matching, Zero-shot CoT reasoning, and mandatory self-critique verification
Patterns and techniques for evaluating and improving AI agent outputs. Use this skill when: - Implementing self-critique and reflection loops - Building evaluator-optimizer pipelines for quality-critical generation - Creating test-driven code refinement workflows - Designing rubric-based or LLM-as-judge evaluation systems - Adding iterative improvement to agent outputs (code, reports, analysis) - Measuring and improving agent response quality
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.
Create diagrams and visual explanations with iterative render-and-check workflow. Use when asked to 'create a diagram', 'Venn diagram', 'flow chart', 'architecture diagram', 'visualize this'. Renders SVG to PNG, self-critiques using CRAP principles, iterates until right. Composes with brand skills for styling. (user)
Launch multiple sub-agents in parallel to execute tasks across files or targets with intelligent model selection and quality-focused prompting