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Found 36 Skills
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.
Generate a smart bootstrap prompt to continue the current conversation in a fresh session. Use when (1) approaching context limits, (2) user says "handoff", "bootstrap", "continue later", "save session", or similar, (3) before closing a session with unfinished work, (4) user wants to resume in a different environment. Outputs a clipboard-ready prompt capturing essential context while minimizing tokens.
For the creation, review, refactoring, and presentation of .ipynb Notebooks (Jupyter / JupyterLab / Google Colab / VS Code). Covers engineered directory structures, efficient token processing, demonstration/sharing patterns, and reproducible workflows with uv/venv.
Token-efficient model routing modifier
Optimize AGENTS.md and rules for token efficiency. Auto-invoked when user asks about improving agent instructions, compressing AGENTS.md, or making rules more effective.
Active diagnostic tool for analyzing skill prompts to identify token waste, anti-patterns, trigger issues, and optimization opportunities. Use when reviewing skill prompts, debugging why skills aren't triggering, optimizing token usage, or preparing skills for publication. Provides specific, actionable suggestions with examples.
Analyzes and improves LLM prompts and agent instructions for token efficiency, determinism, and clarity. Use when (1) writing a new system prompt, skill, or CLAUDE.md file, (2) reviewing or improving an existing prompt for clarity and efficiency, (3) diagnosing why a prompt produces inconsistent or unexpected results, (4) converting natural language instructions into imperative LLM directives, or (5) evaluating prompt anti-patterns and suggesting fixes. Applies to all LLM platforms (Claude, GPT, Gemini, Llama).
Use when writing instructions that guide Claude behavior - skills, CLAUDE.md files, agent prompts, system prompts. Covers token efficiency, compliance techniques, and discovery optimization.
Advanced context engineering techniques for AI agents. Token-efficient plugins improving output quality through structured reasoning, reflection loops, and multi-agent patterns.
balancing accuracy with token efficiency.