GITHUB AGENT SKILLS / 技能收录
给你的 AI 助手
装上专业技能
我们从 GitHub 持续收录、审核并分类优质的 Agent Skills，按职业与使用场景整理，复制一行命令即可安装到 Claude Code、Cursor 等智能体。
按职业浏览 Agent Skills
为不同岗位挑选的高频技能
按使用场景浏览 Agent Skills
从你要完成的任务出发
按创作者浏览 Agent Skills
按 GitHub Stars 排序的优秀创作者
Microsoft
@microsoft
openclaw
@openclaw
OpenAI
@openai
The Apache Software Foundation
@apache
GitHub
@github
Anthropic
@anthropics
AutoGPT
@Significant-Gravitas
Garry Tan
@garrytan全部 Skills 196589
testing-course-samples
暂无简介
microsoft-docs
Consultar a documentação oficial da Microsoft para encontrar conceitos, tutoriais e exemplos de código sobre Azure, .NET, Agent Framework, Aspire, VS Code, GitHub e mais. Utiliza o Microsoft Learn MCP como padrão, com Context7 e Aspire MCP para conteúdo que não está no learn.microsoft.com.
local-ai-agents
暂无简介
jupyter-notebook
暂无简介
deploying-scalable-agents
Take a working agent prototype to a scalable, observable production deployment on Microsoft Foundry. Covers deployment patterns, the agent lifecycle, model routing, response caching, evaluation gates, human approval, OpenTelemetry observability, cost optimisation, and smoke-testing deployed agents.
azure-openai-to-responses
暂无简介
testing-course-samples
暂无简介
microsoft-docs
暂无简介
local-ai-agents
暂无简介
jupyter-notebook
Użyj, gdy użytkownik prosi o utworzenie, przygotowanie szkieletu lub edycję notatników Jupyter (`.ipynb`) do eksperymentów, eksploracji lub samouczków; preferuj dołączone szablony i uruchom skrypt pomocniczy `new_notebook.py`, aby wygenerować czysty notebook początkowy.
deploying-scalable-agents
暂无简介
azure-openai-to-responses
暂无简介
testing-course-samples
Use wen dem ask you to validate, test, smoke-test, or run di course notebook and code samples against live Microsoft Foundry / Azure OpenAI configuration. E cover environment setup (.env, az login, packages), di scripts/validate-notebooks.ps1 runner, how to understand PASS/FAIL results, and which lessons need extra resources (Azure AI Search, GitHub MCP, Foundry Local, Playwright).
microsoft-docs
Query di official Microsoft documentation to find concepts, tutorials, and code examples for Azure, .NET, Agent Framework, Aspire, VS Code, GitHub, and more. Dem dey use Microsoft Learn MCP as di default, plus Context7 and Aspire MCP for content wey no dey inside learn.microsoft.com.
local-ai-agents
Build local-first AI agents wey dey run fully for developer workstation wit Microsoft Foundry Local and Qwen function-calling models. E cover Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG wit Chroma, local MCP servers, hybrid cloud/local routing, and di privacy/cost/offline trade-offs. E based on Lesson 17 of AI Agents for Beginners. USE FOR: run agent locally, offline agent, on-device agent, Foundry Local, Qwen function calling, local tool calling, local RAG, Chroma vector database, local MCP server, privacy-preserving agent, hybrid local and cloud agent, small language model agent, engineering assistant for my machine. DO NOT USE FOR: deploying agents to di cloud at scale (use deploying-scalable-agents / Lesson 16), building your first agent concept (Lesson 01), Foundry (cloud) hosted agents, GPU cluster / server-side inference provisioning.
jupyter-notebook
Use dis one wen di user dey ask make you create, scaffold, or edit Jupyter notebooks (`.ipynb`) for experiments, explorations, or tutorials; prefer di bundled templates and run di helper script `new_notebook.py` make e generate a clean starting notebook.
deploying-scalable-agents
Take one working agent prototype go scalable, observable production deployment for Microsoft Foundry. E cover deployment patterns (client-hosted, hosted agents, agent workflows), the agent lifecycle, model routing, response caching, evaluation gates, human-in-the-loop approval, observability with OpenTelemetry, cost optimisation, and smoke-testing deployed agents with the AI Smoke Test action. Based on Lesson 16 of AI Agents for Beginners. USE FOR: deploy one agent go production, scale one agent, Microsoft Foundry hosted agent, Foundry Agent Service, model routing, response caching, evaluation gate, release gate, human approval workflow, agent observability, agent tracing, agent cost optimisation, smoke test one hosted agent, production customer support agent. DO NOT USE FOR: building your first agent (start with Lesson 01), running agents locally on-device (use local-ai-agents / Lesson 17), Azure infrastructure provisioning we no relate to agents, non-Foundry deployment targets.
azure-openai-to-responses
Shift Python apps dem from Azure OpenAI Chat Completions go Responses API. E cover AzureOpenAI/AsyncAzureOpenAI client shift go v1 endpoint, streaming, tools, structured output, multi-turn, EntraID auth, plus model compatibility checks. Na Python-focused, Azure OpenAI-specific. USE FOR: shift go responses API, change from chat completions, openai responses, upgrade openai SDK, responses API migration, move from completions go responses, gpt-5 migration, azure openai python migration, chat completions go responses, AzureOpenAI go OpenAI client, python azure openai upgrade. DO NOT USE FOR: build new apps from scratch (start with responses directly), Node/TypeScript/C#/Java/Go migrations (dis skill na Python-only), Azure infrastructure setup (use azure-prepare), deploy models (use microsoft-foundry).