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
docs/interactive-responses.md4.4 KiB
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
experts/bridge/commands-slash-text-ts.md18.5 KiB
experts/bridge/cross-platform-advisor-ts.md36.4 KiB
experts/bridge/cross-platform-architecture-ts.md8.3 KiB
experts/bridge/events-activities-ts.md22.4 KiB
experts/bridge/files-upload-download-ts.md17.2 KiB
experts/bridge/identity-oauth-bridge-ts.md19.8 KiB
experts/bridge/index.md13.0 KiB
experts/bridge/infra-compute-ts.md14.6 KiB
experts/bridge/infra-observability-ts.md14.0 KiB
experts/bridge/infra-secrets-config-ts.md13.2 KiB
experts/bridge/infra-storage-ts.md14.3 KiB
experts/bridge/interactive-responses-ts.md19.6 KiB
experts/bridge/link-unfurl-preview-ts.md17.1 KiB
experts/bridge/middleware-handlers-ts.md15.4 KiB
experts/bridge/python-cross-platform.md9.3 KiB
experts/bridge/rate-limiting-resilience-ts.md17.6 KiB
experts/bridge/rest-only-integration-ts.md8.4 KiB
experts/bridge/scheduling-deferred-send-ts.md17.8 KiB
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
experts/convert/dependency-mapping-ts.md8.3 KiB
experts/convert/index.md3.5 KiB
experts/convert/java-to-ts-ts.md20.6 KiB
experts/convert/js-to-ts-ts.md6.2 KiB
experts/convert/json-serialization-ts.md11.0 KiB
experts/convert/kotlin-to-ts-ts.md11.2 KiB
experts/convert/ruby-to-ts-ts.md9.7 KiB
experts/convert/type-mapping-ts.md10.1 KiB
experts/deploy/aws-bot-deploy-ts.md14.6 KiB
experts/deploy/aws-cli-reference-ts.md52.4 KiB
experts/deploy/azure-bot-deploy-ts.md15.4 KiB
experts/deploy/azure-cli-reference-ts.md16.9 KiB
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experts/index.md18.9 KiB
experts/models/anthropic-ts.md7.8 KiB
experts/models/bedrock-ts.md9.9 KiB
experts/models/foundry-cloud-ts.md8.1 KiB
experts/models/foundry-local-ts.md10.6 KiB
experts/models/index.md5.8 KiB
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
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experts/slack/cli.app-management.md7.9 KiB
experts/slack/cli.datastore-env.md8.6 KiB
experts/slack/cli.getting-started.md8.0 KiB
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experts/slack/runtime.ack-rules-ts.md9.8 KiB
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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
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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
experts/teams/ai.function-calling-implementation-ts.md7.7 KiB
experts/teams/ai.memory-localmemory-ts.md7.3 KiB
experts/teams/ai.model-setup-ts.md6.6 KiB
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experts/teams/graph.usergraph-appgraph-ts.md9.0 KiB
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experts/teams/mcp.client-basics-ts.md9.5 KiB
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experts/teams/project.scaffold-files-ts.md12.2 KiB
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experts/teams/state.storage-patterns-ts.md9.4 KiB
experts/teams/teams-dotnet.md8.2 KiB
experts/teams/teams-python.md8.3 KiB
experts/teams/ui.adaptive-cards-ts.md12.9 KiB
experts/teams/ui.dialogs-task-modules-ts.md15.1 KiB
experts/teams/ui.message-extensions-ts.md15.6 KiB
experts/teams/workflow.approvals-inline-ts.md12.4 KiB
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experts/README.md

Bot Platform Expert System

A curated knowledge base for building conversational bots and AI agents across Slack and Microsoft Teams. These micro-experts guide AI coding assistants (Claude, Copilot, etc.) to produce correct, idiomatic code by loading only the relevant expertise for each task.

Goals

Accelerate bot development by giving AI assistants deep, verified knowledge of both Slack and Teams SDKs — eliminating hallucinated APIs and outdated patterns.
Support cross-platform scenarios where a single team needs to ship bots on both Slack and Teams from the same codebase.
Cover the full stack from SDK initialization and webhook plumbing through AI integration, media handling, and infrastructure migration — not just "hello world" examples.
Stay language-pragmatic by focusing on TypeScript (the only language with first-class SDK support on both platforms) while providing REST-level guidance for Java, C#, Go, and other languages.

SDK Language Matrix

Language	Slack Bolt	Teams SDK	Recommendation
TypeScript / JS	Full	Full	Best choice for dual-platform — both SDKs are first-class
Python	Full	Preview	Good for AI/ML workloads; Teams SDK still maturing
Java / JVM	Full	None	Use REST-only patterns for Teams (see `rest-only-integration`)
C# / .NET	None	Full	Use REST-only patterns for Slack (see `rest-only-integration`)
Go, Ruby, etc.	None	None	REST-only for both platforms

Scenarios

1. Build a Teams bot (TypeScript)

Load the Teams domain. 28 micro-experts cover app initialization, routing, Adaptive Cards, dialogs, message extensions, OAuth/SSO, Graph API, AI (ChatPrompt, function calling, RAG, streaming, memory), MCP, A2A, and more.

Key experts: teams/runtime.app-init-ts.md, teams/runtime.routing-handlers-ts.md, teams/ui.adaptive-cards-ts.md

2. Build a Slack bot (TypeScript)

Load the Slack domain. 7 micro-experts cover Bolt.js app setup, handler registration, ack rules, slash commands, Block Kit UI, Events API, Assistant containers, and OAuth/multi-workspace distribution.

Key experts: slack/runtime.bolt-foundations-ts.md, slack/bolt-events-ts.md, slack/bolt-assistant-ts.md

3. Host both bots in a single server

Load the Bridge domain's architecture cluster. Covers shared Express server with route separation, Socket Mode + HTTP dual receiver, platform-agnostic service layer, and identity normalization.

Key expert: bridge/cross-platform-architecture-ts.md

4. Integrate from Java, C#, or Go (no native SDK)

Load the Bridge domain's REST-only cluster. Language-agnostic pseudocode for Bot Framework REST API (Teams) and Slack Events API + Web API — manual JWT validation, HMAC signature verification, token acquisition, and message sending.

Key expert: bridge/rest-only-integration-ts.md

5. Bridge features between Slack and Teams

Load the Bridge domain. 25 micro-experts cover bidirectional mapping of every feature: Block Kit ↔ Adaptive Cards, commands, events ↔ activities, identity, modals ↔ dialogs, files, shortcuts ↔ extensions, workflows ↔ Power Automate, infrastructure (Lambda ↔ Functions, S3 ↔ Blob), and more.

Key expert: bridge/cross-platform-advisor-ts.md (orchestrates the full bridging workflow)

6. Deploy your bot to Azure or AWS

Load the Deploy domain. The router interviews you on cloud provider preference (Azure or AWS) and bot platform (Teams, Slack, or both), then loads the matching expert for a step-by-step walkthrough from CLI installation through verified deployment.

Key experts: deploy/azure-bot-deploy-ts.md, deploy/aws-bot-deploy-ts.md

7. Convert code from another language to TypeScript

Load the Convert domain. 8 micro-experts cover JS→TS, Ruby→TS, Java→TS, Kotlin→TS, type mapping, dependency mapping, JSON serialization, and bulk conversion strategy.

Key experts: convert/java-to-ts-ts.md, convert/kotlin-to-ts-ts.md, convert/type-mapping-ts.md

Expert Inventory

Root (6 files)

File	Purpose
`index.md`	Root task router — interviews developer, routes to domain
`fallback.md`	Recovery when no domain matches
`_expert-ts.md`	Template for creating new experts
`researcher.md`	Deep research workflow for fleshing out experts
`analyzer.md`	Analyze project and recommend new experts
`builder.md`	Build new experts from analysis recommendations

Slack Domain (18 files)

Covers: Bolt.js foundations, ack rules, slash commands, shortcuts, Socket Mode, Block Kit, modals lifecycle, events API, assistant containers, OAuth/distribution, Web API/proactive messaging, Slack CLI (getting started, app management, manifest/triggers, datastore/env, local dev/deploy), Bolt for Python, Bolt for Java.

Teams Domain (35 files)

Covers: app init, routing, manifest, proactive messaging, Adaptive Cards, dialogs, message extensions, OAuth/SSO, Graph API, state/storage, AI (ChatPrompt, model setup, function calling, RAG, streaming, citations, memory), MCP (server, client, security, expose tools), A2A (server, client, orchestrator), BotBuilder interop, debug/test, scaffolding, Agents Toolkit (playground, environments, lifecycle CLI, publish), Teams for Python, Teams for .NET.

Bridge Domain (26 files)

Covers: Block Kit ↔ Adaptive Cards, commands, events ↔ activities, identity/OAuth bridge, middleware ↔ handlers, modals ↔ dialogs, App Home ↔ personal tab, legacy attachments, transport, infrastructure (compute, storage, secrets, observability), interactive responses, files, link unfurl ↔ preview, shortcuts ↔ extensions, scheduling, channel ops, workflows ↔ automation, distribution/packaging, rate limiting, cross-platform advisor, cross-platform architecture, REST-only integration, Python cross-platform.

Convert Domain (8 files)

Covers: JS→TS, Ruby→TS, Java→TS, Kotlin→TS, type mapping, dependency mapping, JSON serialization, bulk conversion strategy.

Models Domain (7 files)

Covers: OpenAI/Azure OpenAI, Anthropic, AWS Bedrock, Azure AI Foundry (cloud), Foundry Local, OSS/OpenAI-compatible, Transformers.js.

Deploy Domain (4 files)

Covers: Azure deployment (App Service, Functions, Agents Toolkit), AWS deployment (Lambda, API Gateway, ECS, SAM), Azure CLI reference, AWS CLI reference.

Security Domain (2 files)

Covers: input validation, secrets management.

How It Works

Developer sends a task → root index.md interviews for scope and preferences
Signal words are scanned → task routes to exactly one domain router
Domain router matches clusters → loads only the relevant micro-expert files
Expert-level interviews (if present) → clarify implementation decisions
Implementation → expert rules, patterns, and pitfalls guide code generation

Eval Harness

The evals/ directory contains an automated test harness that validates the expert system across three dimensions:

Dimension	What it checks	LLM required?
Patterns	TypeScript code blocks in experts still compile	No
Routing	User queries route to the correct domain/clusters/experts	Optional (improves accuracy)
Completeness	Experts cover all required concepts for their domain	Yes

cd evals && npm install
npm run eval:patterns    # fast, no API key
npm run eval             # all dimensions (needs OPENAI_API_KEY in .env)

Current results: 294/294 patterns compile, 41/51 routing cases pass (all 7 domains covered), 9/9 completeness cases pass. The ~10 routing failures are LLM judge scoring edge cases where the deterministic router is correct but the judge scores conservatively on ambiguous or cross-domain queries. See evals/README.md for details.

After adding or editing experts, run npm run eval:patterns to verify code examples still compile. For new domains or significant expert changes, add test cases to evals/cases/ and run the full suite.

Adding New Experts

Use the analyzer.md → builder.md workflow:

Run analyzer.md against a codebase to identify coverage gaps
Hand off recommendations to builder.md to create expert files
New experts auto-wire into domain routers via the post-creation checklist in _expert-ts.md
Run cd evals && npm run eval:patterns to verify new code examples compile

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