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Found 32 Skills
You are an expert prompt engineer specializing in crafting effective prompts for LLMs through advanced techniques including constitutional AI, chain-of-thought reasoning, and model-specific optimizati
Template-based AI prompt engine with YAML templates, brand kit injection, input sanitization for security, and token-efficient context blocks.
Search Tool Hierarchy
Use RepoPrompt CLI for token-efficient codebase exploration
Token-efficient code analysis via 5-layer stack (AST, Call Graph, CFG, DFG, PDG). 95% token savings.
Choose the right search tool for each query type
Optimize agent skills to reduce context bloat while preserving answer coverage. Use when: (1) A skill's SKILL.md body exceeds ~250 lines or duplicates its references/ files (2) A skill's YAML description is verbose or triggers false positives from sibling skills (3) Planning or executing a body/reference split for a skill (4) Auditing skill token efficiency
Use when users say "create a skill", "make a new skill", "build a skill", "skill for X", "package this as a skill", or when refactoring/updating/auditing existing skills that extend agent capabilities with specialized knowledge, workflows, or tool integrations.
Prompt engineering and optimization for AI/LLMs. Capabilities: transform unclear prompts, reduce token usage, improve structure, add constraints, optimize for specific models, backward-compatible rewrites. Actions: improve, enhance, optimize, refactor, compress prompts. Keywords: prompt engineering, prompt optimization, token efficiency, LLM prompt, AI prompt, clarity, structure, system prompt, user prompt, few-shot, chain-of-thought, instruction tuning, prompt compression, token reduction, prompt rewrite, semantic preservation. Use when: improving unclear prompts, reducing token consumption, optimizing LLM outputs, restructuring verbose requests, creating system prompts, enhancing prompt clarity.
Reviews and grades an agent skill directory (SKILL.md plus supporting resources) for specification compliance, clarity, token efficiency, safety, robustness, and portability. Use when a user wants a rubric-based critique with a weighted score/grade and concrete, minimal patch suggestions.
Bulk grading workflows for Canvas LMS assignments using rubrics. Covers single grading, batch grading, and code execution strategies with safety-first dry runs.
Design effective Claude Code skills with optimal descriptions, progressive disclosure, and error prevention patterns. Covers freedom levels, token efficiency, and quality standards. Use when: creating new skills, improving skill descriptions, optimizing token usage, structuring skill content, or debugging why skills aren't being discovered.