Teams App Developer

MicrosoftOfficialPublished by Microsoft

Skill
Tool integration
Software development
MIT
Medium risk

From the author

Builds, tests, and deploys Microsoft 365 apps and agents for Teams and Copilot. Includes sub-skills for project creation, local testing, cloud deployment, troubleshooting, and Slack-to-Teams migration. USE FOR: Teams agent, bot, tab, message extension, Declarative Agents, Custom Engine Agents, local testing, Agents Playground, Azure resource provision, remote deployment, Slack to Teams migration, cross-platform bot development, Block Kit to Adaptive Cards conversion. DO NOT USE FOR: general web development, non-bot/non-Teams projects.

— the description by Microsoft

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The teams-app-developer skill provides a structured framework for managing the lifecycle of Microsoft 365 agents and Teams applications. It leverages the ATK CLI to handle project scaffolding, local testing via the Agents Playground, cloud provisioning on Azure, and troubleshooting. The skill includes specialized guidance for migrating Slack bots to Teams, including converting Block Kit UI to Adaptive Cards, and provides access to an extensive library of micro-expert documentation for cross-platform development.

What it does

Scaffolds new Microsoft 365 agents and Teams applications from templates.
Facilitates local testing using the Agents Playground or Teams-specific environments.
Automates Azure resource provisioning and cloud deployment workflows.
Provides diagnostic procedures for common authentication and configuration errors.
Supports migration of Slack bots to the Teams platform.
Manages project configuration and environment variables for ATK-based projects.

When to use it

When starting a new Teams app, bot, or Declarative Agent project.
When you need to test an agent locally before deploying to the cloud.
When migrating existing Slack bots to the Microsoft Teams ecosystem.
When troubleshooting deployment or authentication issues in a Teams project.
When you need to provision Azure infrastructure for a Teams application.

Advantages

Streamlines the development lifecycle with standardized CLI commands.
Reduces development time by offering a local testing playground.
Provides expert-level guidance for complex cross-platform migrations.
Ensures consistent configuration management across development environments.
Includes robust error-handling protocols for common platform-specific pitfalls.

Usage examples

“Create a new Teams bot project using the default template.”: The agent will initialize a new project folder, configure the necessary YAML files, and guide you through the initial setup using the ATK CLI.
“How do I migrate my Slack bot to Microsoft Teams?”: The agent will initiate the slack-to-teams workflow, providing access to cross-platform bridging experts and guidance on converting UI components.
“My Teams bot is returning a 401 error, how do I fix it?”: The agent will trigger the troubleshooting workflow, checking your environment variables, tunnel status, and authentication configuration.

Install

Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/microsoft/teams-app-developer/download

Unzip it into the cross-client skills folder of your project:

mkdir -p .agents/skills && unzip teams-app-developer.zip -d .agents/skills

Documentation by Microsoft

Microsoft 365 Agents Toolkit Skill

Build Microsoft 365 agents and Teams apps using the ATK CLI.

AI Behavior Guidelines

Testing Strategy: Recommend Agents Playground first (faster, no M365 needed). Use Teams workflow only if user explicitly requests it.
Environment Variables: NEVER hardcode secrets or make up placeholder values. Always ask users for real values.
Error Handling: Read error messages carefully. Check env/.env.local, .localConfigs, and atk auth list. Common pitfalls:
- AADSTS7000229 → aadApp/create missing generateServicePrincipal: true in YAML — add it and re-provision
- Missing TENANT_ID in .localConfigs → SDK uses wrong token authority → 401 from Bot Connector
- 401 persists after auth fix → devtunnel URL may be blacklisted — create a fresh tunnel
- See troubleshoot/troubleshoot.md for full diagnostic steps
Long-Running Commands — WAIT for completion:
- atk new, atk provision, atk deploy can take several minutes
- Always wait for completion before running the next step (timeout 120000ms+)
Local Service Startup — Hangs terminal (expected):
- npm run dev, npm start, python app.py, devtunnel host, etc. will hang — the process keeps running indefinitely
- ALWAYS run as a background process (isBackground=true) — NEVER use isBackground=false for these commands
- Do NOT wait for it to "finish" — verify startup by checking output for "listening on port" or tunnel URL
- If errors appear, read logs, diagnose, fix, restart
- Use a NEW terminal to launch Agents Playground or open Teams sideloading URL
Monitor App Logs: Periodically check background terminal output for runtime errors. If the app crashes, read the error, fix the root cause, and restart.
Telemetry Tagging: Before running any atk CLI commands, set the session environment variable so all CLI invocations are tagged as skill-initiated:
```
export ATK_CLI_SKILL=true
```
Run this once at the start of the session. All subsequent atk commands in the same terminal will inherit it.

ATK CLI Setup

atk --version  # Must be > 1.1.5-beta

If ATK is not found or version is too old:

npm i -g @microsoft/m365agentstoolkit-cli@beta

CLI Global Options

Option	Meaning	Recommendation
`-i`	Interactive mode	Always use `-i false` in automation to avoid hanging
`-f`	Project folder	Default to be current directory, used when specifying a custom folder. When scaffolding a new project, this is the parent folder where the project folder will be created under.
`-h`	Command help	Use `atk <command> -h` for quick syntax checks

Sub-Skills

Sub-Skill	When to Use	Reference
create-project	Scaffold new project from template, choose template, `atk new`	create-project/create-project.md
test-playground	Test locally with Agents Playground, `agentsplayground`, quick testing	test-playground/test-playground.md
test-teams	Run on Teams, devtunnel, sideload, Teams testing, test in Copilot	test-teams/test-teams.md
provision-deploy	Provision Azure resources, deploy to cloud, `atk provision`, `atk deploy`	provision-deploy/provision-deploy.md
troubleshoot	Fix errors, 401, port conflicts, YAML errors, stale bots	troubleshoot/troubleshoot.md
slack-to-teams	Migrate Slack bot to Teams, cross-platform bridging, Block Kit to Adaptive Cards	slack-to-teams/SKILL.md

MANDATORY: Before executing any workflow, read the corresponding sub-skill document.

Shared References

manifest-and-yaml.md — Project files, YAML config, env vars, .localConfigs flow
commands.md — ATK CLI commands: package, validate, share, collaborate
templates.md — Complete template catalog with language support
experts/ — 100+ micro-expert files: Teams SDK, Slack SDK, cross-platform bridging, deploy, AI models, security, language conversion
docs/ — Platform comparison guides: UI, messaging, identity, infrastructure, feature gaps

Workflow Chains

Match user intent to the smallest valid workflow.

User Intent	Workflow (read in order)
Build new app from scratch	create-project → test-playground
Test existing project locally	test-playground (recommended) or test-teams
Deploy to Azure	provision-deploy
Fix broken bot	troubleshoot → re-test
Migrate Slack bot to Teams	slack-to-teams

MANDATORY: Before executing any slack-to-teams workflow, read slack-to-teams/SKILL.md first. The sub-skill contains a routed expert system with 100+ micro-expert files for cross-platform bot development.

ATK Project Context Resolution

Resolve config values only when missing. If a value is already known in the session, reuse it.

Step 1: Detect ATK Project

If m365agentstoolkit*.yml exists in the current folder, treat it as an ATK project and parse configuration.

Step 2: Resolve Common Configuration

Resolve variables referenced in m365agentstoolkit*.yml. Common variables: AZURE_OPENAI_API_KEY AZURE_OPENAI_ENDPOINT AZURE_OPENAI_DEPLOYMENT_NAME

Step 3: Collect Missing Values

If required values are missing, ask the user for only the missing ones.

Refer to manifest-and-yaml.md for full config-file details.

Files

ATTRIBUTION.mdAdded by AutoGineer906 B
LICENSELicence file added by AutoGineer1.1 KiB
SKILL.md7.6 KiB
create-project/create-project.md8.1 KiB
docs/README.md2.8 KiB
docs/advanced-features.md7.0 KiB
docs/feature-gaps.md46.3 KiB
docs/files-and-links.md4.2 KiB
docs/identity-and-auth.md4.3 KiB
docs/infrastructure.md6.7 KiB
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docs/messaging-and-commands.md4.5 KiB
docs/middleware-and-handlers.md4.4 KiB
docs/ui-components.md6.9 KiB
docs/workflows.md14.4 KiB
experts/README.md8.6 KiB
experts/_expert-ts.md2.2 KiB
experts/analyzer.md14.0 KiB
experts/bridge/app-distribution-packaging-ts.md14.2 KiB
experts/bridge/channel-ops-graph-ts.md15.4 KiB
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experts/bridge/cross-platform-advisor-ts.md36.4 KiB
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experts/bridge/index.md13.0 KiB
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experts/bridge/infra-observability-ts.md14.0 KiB
experts/bridge/infra-secrets-config-ts.md13.2 KiB
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experts/bridge/python-cross-platform.md9.3 KiB
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experts/bridge/shortcuts-extensions-ts.md17.5 KiB
experts/bridge/transport-socketmode-https-ts.md14.3 KiB
experts/bridge/ui-app-home-personal-tab-ts.md14.5 KiB
experts/bridge/ui-block-kit-adaptive-cards-ts.md21.5 KiB
experts/bridge/ui-legacy-attachments-cards-ts.md11.2 KiB
experts/bridge/ui-modals-dialogs-ts.md21.4 KiB
experts/bridge/workflow.composable-platform-ts.md13.7 KiB
experts/bridge/workflows-automation-ts.md14.3 KiB
experts/builder.md11.1 KiB
experts/convert/bulk-conversion-strategy-ts.md12.8 KiB
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experts/convert/index.md3.5 KiB
experts/convert/java-to-ts-ts.md20.6 KiB
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experts/deploy/aws-bot-deploy-ts.md14.6 KiB
experts/deploy/aws-cli-reference-ts.md52.4 KiB
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experts/models/anthropic-ts.md7.8 KiB
experts/models/bedrock-ts.md9.9 KiB
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experts/models/foundry-local-ts.md10.6 KiB
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experts/models/openai-azure-openai-ts.md8.3 KiB
experts/models/oss-openai-compatible-ts.md10.7 KiB
experts/models/transformers-js-ts.md11.6 KiB
experts/prompt-engineer.md14.7 KiB
experts/researcher.md2.8 KiB
experts/security/index.md1.2 KiB
experts/security/input-validation-ts.md13.8 KiB
experts/security/secrets-ts.md13.9 KiB
experts/slack/bolt-assistant-ts.md9.9 KiB
experts/slack/bolt-events-ts.md9.3 KiB
experts/slack/bolt-java.md8.9 KiB
experts/slack/bolt-oauth-distribution-ts.md10.9 KiB
experts/slack/bolt-python.md9.5 KiB
experts/slack/cli.app-management.md7.9 KiB
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experts/slack/cli.manifest-triggers.md9.9 KiB
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experts/slack/runtime.ack-rules-ts.md9.8 KiB
experts/slack/runtime.bolt-foundations-ts.md10.7 KiB
experts/slack/runtime.shortcuts-ts.md11.0 KiB
experts/slack/runtime.slash-commands-ts.md11.6 KiB
experts/slack/runtime.socket-mode-ts.md9.5 KiB
experts/slack/ui.block-kit-ts.md11.5 KiB
experts/slack/ui.modals-lifecycle-ts.md13.3 KiB
experts/slack/web-api-proactive-ts.md11.0 KiB
experts/slack/workflow.slack-automations-ts.md10.2 KiB
experts/teams/a2a.client-basics-ts.md9.7 KiB
experts/teams/a2a.orchestrator-patterns-ts.md12.7 KiB
experts/teams/a2a.server-basics-ts.md11.4 KiB
experts/teams/ai.chatprompt-basics-ts.md8.1 KiB
experts/teams/ai.citations-feedback-ts.md6.9 KiB
experts/teams/ai.conversational-query-ts.md14.2 KiB
experts/teams/ai.function-calling-design-ts.md9.0 KiB
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experts/teams/ai.memory-localmemory-ts.md7.3 KiB
experts/teams/ai.model-setup-ts.md6.6 KiB
experts/teams/ai.rag-retrieval-ts.md7.4 KiB
experts/teams/ai.rag-vectorstores-ts.md8.5 KiB
experts/teams/ai.streaming-ts.md6.9 KiB
experts/teams/auth.oauth-sso-ts.md10.1 KiB
experts/teams/compat.botbuilder-interop-ts.md14.6 KiB
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experts/teams/teams-dotnet.md8.2 KiB
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experts/teams/ui.dialogs-task-modules-ts.md15.1 KiB
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toolkit/lifecycle-cli.md17.6 KiB
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toolkit/templates.md6.7 KiB
troubleshoot/troubleshoot.md20.2 KiB

experts/models/index.md

models-router

purpose

Route AI model integration tasks to the correct provider-specific expert. Covers configuring, calling, and managing AI models from any supported provider: Anthropic, OpenAI, Azure OpenAI, AWS Bedrock, Azure AI Foundry (cloud), Foundry Local, and OpenAI-compatible OSS endpoints (Ollama, vLLM, LM Studio, etc.).

interview

Q1 — Model Provider

question: "Which AI model provider are you working with?"
header: "Provider"
options:
  - label: "OpenAI / Azure OpenAI (Recommended)"
    description: "GPT-4o, GPT-4, GPT-3.5. Works with both OpenAI API and Azure OpenAI Service. Best Teams AI SDK support."
  - label: "Anthropic (Claude)"
    description: "Claude 4, Claude 3.5 Sonnet, Claude 3 Haiku. Direct API or via AWS Bedrock."
  - label: "AWS Bedrock"
    description: "Managed access to Anthropic, Meta Llama, Cohere, Amazon Titan, and other models. Uses AWS IAM auth."
  - label: "Foundry / OSS Local"
    description: "Azure AI Foundry (cloud or local), Ollama, vLLM, LM Studio, or any OpenAI-compatible endpoint for open-source models."
multiSelect: false

Q2 — Use Case

question: "What are you building with the model?"
header: "Use case"
options:
  - label: "Bot / agent with chat completions"
    description: "Chat-style interaction in a Slack or Teams bot. May include function calling / tool use."
  - label: "RAG / knowledge retrieval"
    description: "Retrieve-then-generate pattern with embeddings, vector stores, or knowledge bases."
  - label: "Standalone API integration"
    description: "Direct API calls from a service — not tied to a specific bot framework."
  - label: "You decide everything"
    description: "Use recommended defaults and skip remaining questions."
multiSelect: false

defaults table

Question	Default
Q1	OpenAI / Azure OpenAI
Q2	Bot / agent with chat completions

task clusters

OpenAI / Azure OpenAI

When: OpenAI, Azure OpenAI, GPT-4o, GPT-4, GPT-3.5, openai npm package, @azure/openai, chat completions, OpenAI API key, Azure OpenAI endpoint, deployment name, apiVersion Read:

openai-azure-openai-ts.md Cross-domain deps: ../teams/ai.model-setup-ts.md (Teams AI SDK model config), ../deploy/azure-cli-reference-ts.md (az cognitiveservices for Azure OpenAI provisioning), ../security/secrets-ts.md (API key management)

Anthropic (Claude)

When: Anthropic, Claude, Claude 4, Claude 3.5, Claude 3, @anthropic-ai/sdk, Anthropic API, ANTHROPIC_API_KEY, Messages API, tool use with Claude Read:

anthropic-ts.md Cross-domain deps: ../security/secrets-ts.md (API key management)

AWS Bedrock

When: Bedrock, AWS Bedrock, @aws-sdk/client-bedrock-runtime, Bedrock agents, Bedrock Converse API, Bedrock Knowledge Bases, hosted Anthropic, hosted Llama, Amazon Titan, Bedrock guardrails Read:

bedrock-ts.md Cross-domain deps: ../deploy/aws-cli-reference-ts.md (aws bedrock CLI commands), ../deploy/aws-bot-deploy-ts.md (Lambda/ECS deployment), ../security/secrets-ts.md (IAM auth)

Azure AI Foundry (Cloud)

When: Azure AI Foundry, AI Foundry, Foundry Models, Azure AI model catalog, model-as-a-service, MaaS, serverless API, Azure AI Studio, Foundry cloud, GitHub Models Read:

foundry-cloud-ts.md Cross-domain deps: ../deploy/azure-cli-reference-ts.md (az cognitiveservices for provisioning), ../security/secrets-ts.md (API key management)

Foundry Local

When: Foundry Local, foundry CLI, flocal, local model, local inference, run model locally, on-device AI, ONNX, Phi-4, Qwen, foundry model run, foundry model list, foundry service, offline AI Read:

foundry-local-ts.md

OpenAI-Compatible OSS Endpoints

When: Ollama, vLLM, LM Studio, llama.cpp, text-generation-inference, TGI, LocalAI, OpenAI-compatible, self-hosted model, open-source model, Llama, Mistral, DeepSeek, local LLM, /v1/chat/completions custom endpoint, custom base URL Read:

oss-openai-compatible-ts.md

Transformers.js (In-Process Inference)

When: Transformers.js, @huggingface/transformers, in-process inference, browser inference, WASM inference, WebGPU inference, local embeddings, local classification, local NER, local summarization, pipeline API, HuggingFace Hub, ONNX in browser, serverless ML, no-server AI, feature extraction, zero-shot classification, sentiment analysis, token classification, offline embeddings Read:

transformers-js-ts.md Cross-domain deps: openai-azure-openai-ts.md (hybrid pattern — local preprocessing + cloud LLM)

Multi-Provider / Provider Abstraction

When: multiple models, fallback model, model routing, provider abstraction, LangChain, LiteLLM, Vercel AI SDK, ai npm package, model switching, cost optimization, A/B test models Read:

openai-azure-openai-ts.md
anthropic-ts.md
oss-openai-compatible-ts.md

combining rule

If the developer uses multiple providers (e.g., Claude for reasoning + GPT-4o for function calling, or Foundry Local for dev + Azure OpenAI for prod), load all relevant provider experts. The multi-provider cluster above covers this.

If integrating a model into a Teams bot, always also read ../teams/ai.model-setup-ts.md — it covers the OpenAIChatModel wrapper that Teams AI SDK uses.

If integrating a model into a Slack bot, the provider experts here cover direct SDK usage — Slack Bolt doesn't have a built-in AI layer, so you wire models directly.

file inventory

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs an API key, Needs Python, Needs Node.js

Security

What our scanner noticed· Medium risk

Possible data-exfiltration endpoints
Instructions that use the network
Downloads piped into a shell

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by

Microsoft

Publisher

Microsoft (Official)

Source

microsoft/skills · .github/plugins/microsoft-365-agents-toolkit/skills/teams-app-developer · commit 0696600

Licence

MIT License (redistribution allowed)

LICENSE (added by AutoGineer from LICENSE)
ATTRIBUTION.md (written by AutoGineer)

Synced

2026-11-08

AutoGineer is not affiliated with or endorsed by Microsoft.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download teams-app-developer.zip