What is make-ai-teammate?

A workflow that converts an existing AI agent into a Microsoft Agent 365 AI Teammate, an agent that can be hosted and made available through Microsoft workplace products. It supports common .NET, Node.js, and Python frameworks while preserving the existing model and business logic.

Use it to prepare an agent for Microsoft Teams or Copilot, connect its existing logic to Agent 365, and configure the required setup and hosting steps.

It adds the hosting, routing, and notification structure needed for Microsoft 365 access without deleting the agent's current implementation.

make-ai-teammate — Skill for Claude Code by microsoft

About the project

Microsoft Agent 365 Skills is a collection of coding-agent skills and MCP configuration for building and operating AI Teammates hosted in Microsoft Teams. It supports the Agent 365 lifecycle, including WorkIQ integration, registration, observability, validation, and local testing, for users of Claude Code and GitHub Copilot.

microsoft/agent365-skills · 37 stars · on GitHub

Install

Getting it into your agent

This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.

Claude Code

/plugin marketplace add microsoft/agent365-skills

Claude Code

/plugin install agent365

Made for: Claude Code.

Or install agent365, the plugin that ships this one along with the rest of its 7 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/microsoft/agent365-skills/make-ai-teammate/github.svg)](https://agentmods.dev/skills/microsoft/agent365-skills/make-ai-teammate)

Your own site

<a href="https://agentmods.dev/skills/microsoft/agent365-skills/make-ai-teammate"><img src="https://agentmods.dev/badge/skills/microsoft/agent365-skills/make-ai-teammate/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/microsoft/agent365-skills/make-ai-teammate"><img src="https://agentmods.dev/badge/skills/microsoft/agent365-skills/make-ai-teammate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 148 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 14,544 The whole file, excluding the scripts and references it only reads on demand.

Security scan C 1 finding. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00148	$0.14544
Opus 5	$0.00074	$0.07272
Sonnet 5	$0.00030	$0.02909
Haiku 4.5	$0.00015	$0.01454

Measured 10d ago against content hash f1fa8cb8329c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade C, and why

make-ai-teammate scanned grade C with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Recursive force deletehighDestructive command

rm -rf with a variable or a broad path is one typo away from removing the wrong tree.

rm -rf _tmp_a365samples

plugins/agent365/skills/make-ai-teammate/SKILL.md · 1,019 lines

How it starts

The opening of the file, as written. The whole thing — 1,019 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Make AI Teammate

Trigger phrases — any of these will activate this skill:

"make this agent an ai teammate"

"transform this agent into an ai teammate"

"publish this agent to teams"

"make this agent available in microsoft teams"

"publish this agent to microsoft copilot"

"add teams support to this agent"

"set up ai teammate hosting for this agent"

"convert this agent to a teams agent"

"make this agent work with microsoft 365"

What this skill does: It wraps your existing LLM logic with the Microsoft Agent 365 AI Teammate layer — hosting, routing, and notifications. Your existing LLM code (models, prompts, tools, business logic) is preserved and integrated into the new structure. Nothing is deleted.

Prerequisite: Run a365-setup first — it registers the agent with Agent 365 and writes the detection cache that this skill reads.

Supported languages: Node.js (LangChain, OpenAI Agents SDK, Claude SDK, Semantic Kernel, Google ADK) · .NET (AgentFramework, Semantic Kernel) · Python (AgentFramework, LangChain, OpenAI, Claude, Semantic Kernel, Google ADK)

Phase 0A — Workspace Triage and Detection Cache

Step 1 — Triage the workspace

Run in parallel and combine results:

Glob **/*.csproj, package.json, requirements.txt, pyproject.toml, src/**/*.ts, **/*.cs, **/*.py → does any agent code or project file exist? Call this hasProjectFiles.
Read .a365-workspace-detection.local.json → does the cache exist, and is detectedAt within 60 minutes? Call this cacheState (fresh, stale, or missing).
Parse $ARGUMENTS for an explicit framework hint (e.g. dotnet, dotnet-sk, langchain, openai, claude, semantickernel, googleadk, python) and the word create. Store as argFramework and argCreateIntent.

Decide what to do next from this table — do not fall through to Step 2 until one of these branches has run:

`cacheState`	`hasProjectFiles`	Action
`fresh`	—	Continue to Step 2 below (load cache).
`missing`	false	Empty workspace, new-agent path. Tell the user: "This is a fresh workspace — I'll scaffold a starter agent from Agent365-Samples first, then run `a365-setup` to register it." Jump directly to Phase 0A.5. If `argFramework` is set, pre-select the matching sample (e.g. `dotnet` → option 1, `dotnet-sk` → option 2, `langchain` → option 3, etc.) and skip the menu. After scaffolding completes, Read `${CLAUDE_PLUGIN_ROOT}/skills/a365-setup/SKILL.md` and follow it to register the new agent — then return to Step 2 below.
`missing`	true	Tell the user: "I found existing agent code but no Agent 365 registration. I'll run `a365-setup` now to register it and detect its framework, then continue here automatically." Read `${CLAUDE_PLUGIN_ROOT}/skills/a365-setup/SKILL.md` and follow it to completion, then return to Step 2 below.
`stale`	—	Tell the user the detection cache is stale (>60 min) and re-run `a365-setup` the same way as the `missing + true` row, then return to Step 2.

Read the full file on GitHub · 1,019 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

10d ago First seen · 1,019 lines · 148 tokens per session scan C f1fa8cb8329c

Subscribe to this mod's changes

make-ai-teammate is a skill published in the GitHub repository microsoft/agent365-skills (37 stars, last pushed yesterday), licensed MIT. It adds 148 tokens to every session and 14,544 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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