Total 55,837 skills, AI & Machine Learning has 9269 skills
Showing 12 of 9269 skills
AI design workflow with DESIGN.md, anti-patterns, and optional Stitch MCP
Internal guidance for composing Codex and GPT-5.4 prompts for coding, review, diagnosis, and research tasks inside the Codex Claude Code plugin
Watch a tutorial, demo, or walkthrough video and generate a Claude Code skill from it. Extracts the workflow, commands, tools, and patterns demonstrated and produces a SKILL.md with implementation. Supports Loom, YouTube, and local files.
Qdrant provides client SDKs for various programming languages, allowing easy integration with Qdrant deployments.
Use when an approved current phase has 3 or more independent ready tasks and parallel execution will materially reduce cycle time. Orchestrates bounded workers, monitors blockers and file conflicts, coordinates rescues, and hands off to planning or reviewing when the current execution scope is complete. Use for prompts about swarming, parallel workers, launching multiple agents, coordinating a worker pool, or running approved current-phase work at scale.
Targeted Chat Room: Recommend experts based on topics or accept user-specified experts to simulate multi-role conversations. Trigger methods: /定向聊天室, 「定向聊天室」
Add Opik tracing to an existing codebase. Detects language (Python/TypeScript), identifies LLM frameworks, adds appropriate decorators and integrations, marks entrypoints, and wires up environment config. Use for "instrument my code", "add opik tracing", "add observability", or "trace my agent".
Validates dataset formatting and quality for SageMaker model fine-tuning (SFT, DPO, or RLVR). Use when the user says "is my dataset okay", "evaluate my data", "check my training data", "I have my own data", or before starting any fine-tuning job. Detects file format, checks schema compliance against the selected model and technique, and reports whether the data is ready for training or evaluation.
Discovers user intent and generates a structured, step-by-step customization plan that orchestrates other skills. Always activate at the start of every conversation, when all tasks in a plan are completed, or when the user asks to modify the current plan. Handles intent discovery, plan generation, plan iteration, and mid-execution plan alterations. When in doubt, use this skill.
Find and resolve prompt files in ./prompts/ directory. Use when user asks to find a prompt, list available prompts, locate prompt by number or name, or check what prompts exist.
Generates a Jupyter notebook that deploys fine-tuned models from SageMaker Serverless Model Customization to SageMaker endpoints or Bedrock. Use when the user says "deploy my model", "create an endpoint", "make it available", or asks about deployment options. Identifies the correct deployment pathway (Nova vs OSS), generates deployment code, and handles endpoint configuration.
Mandatory protocol for dispatching any built-in and custom agent in this project via the task tool. Use this skill EVERY TIME you are about to call the task tool with a custom agent_type. This skill ensures the agent's intended model (declared in its YAML frontmatter) is respected rather than overridden by a default. Also encodes prompting best practices for subagent context and quality. ALWAYS invoke before any task tool call that targets a custom agent — even if the agent name seems obvious.