microsoft/cat-agent-skills is a static website that catalogs reusable instruction sets and related packages for AI agents. People use it to search, filter, rate, and download skills for Cowork, Copilot Studio, and Scout, along with Copilot plugins and Scout automations. The catalogue entries are the skills, instructions, plugins, and settings displayed by the site.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add microsoft/cat-agent-skills --skill microsoft-ai-platform-advisorgit clone --depth 1 https://github.com/microsoft/cat-agent-skillsWrote 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.
[](https://agentmods.dev/skills/microsoft/cat-agent-skills/microsoft-ai-platform-advisor)<a href="https://agentmods.dev/skills/microsoft/cat-agent-skills/microsoft-ai-platform-advisor"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/microsoft-ai-platform-advisor/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.
<a href="https://agentmods.dev/skills/microsoft/cat-agent-skills/microsoft-ai-platform-advisor"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/microsoft-ai-platform-advisor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00125 | $0.03370 |
| Opus 5 | $0.00063 | $0.01685 |
| Sonnet 5 | $0.00025 | $0.00674 |
| Haiku 4.5 | $0.00013 | $0.00337 |
Grade A, and why
microsoft-ai-platform-advisor scanned grade A with 0 findings 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 9d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 252 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Microsoft AI Platform Advisor
What this skill does
Runs a structured discovery interview with the user, maps their answers to the right Microsoft AI platform using official Microsoft guidance, scores the build on technical complexity and risk, then plots those scores on a 2x2 quadrant chart — as an inline Mermaid chart and, when code interpreter is available, as a rendered PNG chart from a Python script. Returns a full recommendation brief the user can save.
Interaction style
- Ask one question at a time. Wait for the answer before moving on.
- Use plain business language. Avoid Microsoft product jargon in the questions themselves.
- Adapt: skip any question whose answer is already implied by an earlier one.
- Aim for 10–12 questions total.
- After the questions, produce the full recommendation brief in one message.
Phase 1 — Discovery questions
Ask these in order. Store each answer for later use.
1. Project name. "What should I call this project? A short label is fine."
2. Audience. "Who is the primary user of this AI solution — just you, a small team, a whole department, the whole company, or external customers?"
3. Existing agent. "Do you already have an AI agent built somewhere else — for example on LangChain, OpenAI Agents SDK, another cloud, or from a vendor — that you want to bring into your Microsoft environment?"
4. Data sources. "What data does the AI need to read? Only Microsoft 365 files like SharePoint and Outlook, Microsoft 365 plus a few external systems, or enterprise data across many custom systems and databases?"
5. Actions. "What should the AI actually do — just answer questions from documents, answer plus take a simple action like sending an email or creating a ticket, run a multi-step workflow with approvals and branching, or operate autonomously without a human checking each step?"
6. Runtime location. "Where does the AI need to run — the cloud is fine, cloud but locked down with your own network isolation, or on the device itself with no cloud connection?"
What ships with it
3 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.
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.
- 9d ago First seen · 252 lines · 125 tokens per session scan A 5b5901101911
microsoft-ai-platform-advisor is a skill published in the GitHub repository microsoft/cat-agent-skills (66 stars, last pushed yesterday), licensed MIT. It adds 125 tokens to every session and 3,370 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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