Total 56,891 skills, AI & Machine Learning has 9461 skills
Showing 12 of 9461 skills
Complete AI agent operating system setup with Kanban task management. Use when setting up multi-agent coordination, task tracking, or configuring an agent team. Includes theme selection (DBZ, One Piece, Marvel, etc.), workflow enforcement (all tasks through board), browser setup, GitHub integration, and memory enhancement (mem0, Supermemory, QMD).
Expert guidance for OpenAI API development including GPT models, Assistants API, function calling, embeddings, and best practices for production applications.
Create effective skills for OpenCode agents. Load FIRST before writing any SKILL.md. Provides required format, naming conventions, progressive disclosure patterns, and validation. Use when building, reviewing, or debugging skills.
Build automated evaluation suites for AI agents using golden datasets, rubrics, and regression gates.
Build autonomous RAG agents that reason, plan, and use tools for complex retrieval tasks. Use this skill when simple retrieve-and-generate isn't enough. Activate when: agentic RAG, RAG agent, multi-step retrieval, tool-using RAG, autonomous retrieval, query decomposition.
OpenSpec Spec-Driven Development Assistant - An AI-aided programming framework based on the OPSX workflow. Align requirements with AI before writing code, and manage changes using a Schema-driven artifact dependency system. Trigger Conditions: 1. User mentions "openspec", "opsx", or spec-driven development 2. User wants to start new feature development or refactoring 3. User needs to explore complex problems or clarify requirements 4. User complains about AI misunderstanding or frequent rework 5. User uses slash commands such as /opsx:new, /opsx:ff, /opsx:apply, etc. 6. During project initialization or preparation for major changes
Expert prompt engineering for creating effective prompts for Claude, GPT, and other LLMs. Use when writing system prompts, user prompts, few-shot examples, or optimizing existing prompts for better performance.
Frames coding-agent work sessions with explicit intent capture and drift monitoring. Use when a session transitions from planning/Q&A to implementation for coding tasks, refactors, feature builds, bug fixes, or other multi-step execution where scope drift is a risk.
Execute this skill should be used when the user asks about "SPAWN REQUEST format", "agent reports", "agent coordination", "parallel agents", "report format", "agent communication", or needs to understand how agents coordinate within the sprint system. Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.
Create AI evaluation plans with benchmarks, rubrics, and error analysis workflows.
Structured checkpoint format for requesting human input. When an agent needs a decision, it must stop, present context, show options, and wait. Activate when delegating to subagents, running background tasks, or hitting any decision point that requires human judgment.
Guide for creating effective skills for AI coding agents working with Azure SDKs and Microsoft Foundry services. Use when creating new skills or updating existing skills.