Total 32,491 skills, AI & Machine Learning has 5242 skills
Showing 12 of 5242 skills
Instructions for AI agents to create new skills and add them to the skills repository
Enables Claude to read, compose, search, and manage emails in Gmail via Playwright MCP
Analyze the current session and propose improvements to skills. **Proactively invoke this skill** when you notice user corrections after skill usage, or at the end of skill-heavy sessions. Also use when user says "reflect", "improve skill", or "learn from this".
Generate videos with Model Studio DashScope SDK using the wan2.6-i2v-flash model. Use when implementing or documenting video.generate requests/responses, mapping prompt/negative_prompt/duration/fps/size/seed/reference_image/motion_strength, or integrating video generation into the video-agent pipeline.
Requirements Discovery Specification, applicable to exploratory scenarios, helps users identify high-ROI functional directions when they are confused through role-playing. Automatically triggered, purely conversational inspiration.
After the task execution is completed, prompt the user to open a new Agent to review the uncommitted git code. Athletes should not act as referees; proceed with the wrap-up only after the review is approved.
CUDA kernel development, debugging, and performance optimization for Claude Code. Use when writing, debugging, or optimizing CUDA code, GPU kernels, or parallel algorithms. Covers non-interactive profiling with nsys/ncu, debugging with cuda-gdb/compute-sanitizer, binary inspection with cuobjdump, and performance analysis workflows. Triggers on CUDA, GPU programming, kernel optimization, nsys, ncu, cuda-gdb, compute-sanitizer, PTX, GPU profiling, parallel performance.
Workflow Checkpoint Basic Capabilities (Focus on Save and Resume): Record checkpoint progress and resume context in GitHub Issues. Applicable to any workflow stage, supporting automatic triggering and high-frequency manual calls. Keywords: save, resume, checkpoint, issue.
Expert prompt engineering for LLM applications including prompt design, optimization, RAG systems, agent architectures, and AI product development.
Expert ML engineering covering model development, MLOps, feature engineering, model deployment, and production ML systems.
Systematically reduce the AI detection rate to below 30%, and add a human touch through a three-round review process (content, style, details). Use this skill when users mention phrases such as "too AI-like", "sounds written by AI", "reduce AI detection rate", "more human-like", "more natural", or "colloquial"
This skill should be used when conducting comprehensive research on any topic using the OpenAI Deep Research API. It automates prompt enhancement through interactive clarifying questions, saves research parameters, and executes deep research with web search capabilities. Use when the user asks for in-depth analysis, investigation, research summaries, or topic exploration.