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Agent Skill · 开发

teams-sdk-project(teams SDK project 命令行)

teams-sdk-project 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

teams-sdk-project 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描有未通过项,按安装量在开发类的 21,746 个 Skill 里排第 19,580。

总安装 267周安装 11GitHub Stars 公开资料未说明下载 87核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:teams-sdk-project(teams SDK project 命令行)
来源仓库:https://github.com/heyitsaamir/teams.ts-skills
仓库路径:skills/teams-sdk-project
安装命令:
npx skills add https://github.com/heyitsaamir/teams.ts-skills --skill teams-sdk-project
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/heyitsaamir/teams.ts-skills --skill teams-sdk-project

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

teams-sdk-project 用于处理 GitHub 仓库、Issue 和 Pull Request。适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态进行协作整理。通过 npx skills add 命令从指定仓库安装并使用。

安装前需确认权限范围、维护状态及是否触发联网或文件读写。建议结合原始 README 核验具体用法和功能边界。

来源仓库内路径:skills/teams-sdk-project

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/heyitsaamir/teams.ts-skills --skill teams-sdk-…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

teams-sdk-project 怎么安装?

在终端执行 npx skills add https://github.com/heyitsaamir/teams.ts-skills --skill teams-sdk-project。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

teams-sdk-project 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

teams-sdk-project 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

teams-sdk-project 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

teams-sdk-project 用的人多吗?

公开数据是累计安装 267 次,近一周安装 11 次,下载 87 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

teams-sdk-project 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
teams-sdk-project

teams SDK project 命令行 · 本页

267—接触敏感数据未明确未通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Teams SDK Project Scaffolding

This skill walks developers through the full end-to-end process of creating a Teams bot project in TypeScript — from dev tunnel setup through bot registration to a running, message-handling bot.

Overview

There are three phases to getting a Teams bot running:

  1. Dev Tunnel — Create a public tunnel so Teams can reach your local server
  2. Bot Registration — Use the teams2 CLI to register an Azure AD app, create a bot, and get credentials
  3. Project Scaffolding — Generate the TypeScript project files and wire everything together

Phase 1: Dev Tunnel

The bot needs a publicly accessible HTTPS endpoint. Teams sends messages to this URL. During development, a tunnel forwards traffic from a public URL to localhost:3978.

Ask the user which tunnel provider they prefer, then follow the appropriate section.

Option A: Microsoft Dev Tunnels (devtunnel)

Check if devtunnel is installed by running devtunnel --version. If not installed:

brew install microsoft/dev-tunnels/devtunnel

Check if the user is logged in with devtunnel user show. If not:

devtunnel user login

Create the tunnel — run these commands to create a named, persistent tunnel. Use the project name as the tunnel name:

devtunnel create <tunnel-name> -a
devtunnel port create <tunnel-name> -p 3978

Get the tunnel URL — run this to retrieve the endpoint URL (available immediately after creation, before hosting):

devtunnel show <tunnel-name>

Parse the "Connect via browser" URL from the output. It will look like https://<tunnel-name>-3978.<region>.devtunnels.ms. Save this — it's used as the bot endpoint in Phase 2.

Option B: ngrok

Tell the user to run ngrok in a separate terminal (long-running process):

brew install ngrok   # if not installed
ngrok http 3978

The user needs to share the forwarding URL (e.g., https://abc123.ngrok-free.app) back before proceeding.

Phase 2: Bot Registration with teams2 CLI

Check if teams2 is installed by running teams2 --version. If not installed:

npm install -g https://github.com/heyitsaamir/teamscli/releases/latest/download/teamscli.tgz

Check if the user is logged in with teams2 status. If not, run:

teams2 login

This opens a device-code authentication flow — the user needs to complete the browser authentication step.

Create the bot — run this using the tunnel URL from Phase 1. Write the .env file into the project directory:

teams2 app create -n "<project-name>" -e https://<tunnel-url>/api/messages --env <project-dir>/.env

This command automatically:

  1. Creates an Azure AD app registration
  2. Generates a client secret
  3. Registers the bot in the Teams Developer Portal
  4. Imports the app package with manifest
  5. Writes CLIENT_ID and CLIENT_SECRET to the .env file

After creation, read the CLIENT_ID from the .env file and show the Teams install link:

teams2 app view <CLIENT_ID> --web

Share this install link with the user so they can install the bot in Teams later.

Phase 3: Project Scaffolding

Ask the user which template they want:

  • Echo — Simple bot that echoes back messages. Good starting point.
  • AI — Bot with OpenAI/Azure OpenAI integration, streaming, and conversation memory. For building intelligent agents.

Then scaffold the project by creating the files described in the appropriate reference:

  • Echo template: read references/echo-template.md
  • AI template: read references/ai-template.md

Install dependencies after scaffolding:

cd <project-dir> && npm install

For the AI template, the user also needs to add their OpenAI/Azure OpenAI credentials to .env.

Getting it Running

Once everything is scaffolded, tell the user to run two commands in separate terminals:

  1. Host the tunnel (if using devtunnel): devtunnel host <tunnel-name>
  2. Start the bot: npm run dev

The bot is now live. The install link was already shown after bot registration in Phase 2 — remind the user to open it in Teams to start chatting with the bot.

Project Structure

Both templates produce this structure:

<project-name>/
├── src/
│   └── index.ts          # Bot entry point
├── .env                   # Credentials (from teams2)
├── package.json
├── tsconfig.json
└── tsup.config.js

Environment Variables Reference

Echo bot

VariableDescriptionSource
CLIENT_IDAzure AD app client IDteams2 app create
CLIENT_SECRETAzure AD app client secretteams2 app create
PORTServer port (default: 3978)Optional

AI bot (additional)

VariableDescriptionSource
OPENAI_API_KEYOpenAI API keyUser provides
AZURE_OPENAI_API_KEYAzure OpenAI API key (alternative)User provides
AZURE_OPENAI_ENDPOINTAzure OpenAI endpoint URLUser provides
AZURE_OPENAI_API_VERSIONAzure OpenAI API versionUser provides
AZURE_OPENAI_MODEL_DEPLOYMENT_NAMEAzure OpenAI deployment nameUser provides

Key SDK Concepts

The App class

The App from @microsoft/teams.apps is the main entry point. It handles HTTP server setup, authentication, and activity routing.

Event handlers

Register handlers with app.on(eventName, handler):

  • 'message' — User sends a message
  • 'install.add' — Bot is installed
  • 'message.submit.feedback' — User gives feedback on a message

Handler parameters: {send, reply, stream, activity, next, log}

  • send(activity) — Send a new message
  • reply(activity) — Reply to the current message
  • stream.emit(chunk) — Stream a response chunk
  • activity — The incoming activity/message
  • next() — Pass to the next handler (middleware pattern)
  • log — Logger instance

AI capabilities (AI template)

  • ChatPrompt from @microsoft/teams.ai — Manages LLM conversations with system instructions and message history
  • OpenAIChatModel from @microsoft/teams.openai — Connects to OpenAI or Azure OpenAI
  • .addAiGenerated() on MessageActivity — Marks response as AI-generated in Teams UI
  • Streaming via onChunk callback and stream.emit()

Plugins

  • DevtoolsPlugin from @microsoft/teams.dev — Adds development tooling and debugging support

平台分布

Codex

33.41%
按下载量换算29

Claude

30.87%
按下载量换算27

Cursor

20.37%
按下载量换算18

Gemini CLI

9.38%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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