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 stakeholder-qa-prepgit 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/stakeholder-qa-prep)<a href="https://agentmods.dev/skills/microsoft/cat-agent-skills/stakeholder-qa-prep"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/stakeholder-qa-prep/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/stakeholder-qa-prep"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/stakeholder-qa-prep.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00141 | $0.01325 |
| Opus 5.5 | $0.00056 | $0.00530 |
| Sonnet 5.5 | $0.00028 | $0.00265 |
| Haiku 4.5 | $0.00014 | $0.00133 |
Grade A, and why
stakeholder-qa-prep 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 2d 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Stakeholder Q&A Prep
Pre-drafts the questions a senior stakeholder is most likely to ask, with a short answer for each anchored to a real number — and an honest marker where the answer isn't known yet.
When NOT to Use
- General meeting prep across all meeting types → outside this skill's scope
- Building the review pre-read or brief → use
forecast-review-prep - Answering questions already received in an email or chat → just answer them directly
- Rehearsing a personnel or performance conversation — out of scope entirely
Related Skills
Hand off rather than overlap:
- The review pre-read or brief — use forecast-review-prep instead.
- A slide-format prep pack — use pptx instead.
- Outbound stakeholder messaging — outside this skill's scope.
- General meeting prep of any type — outside this skill's scope.
Workflow
1. Identify the review and the audience
Establish which meeting and who the primary audience is. Resolve named people with
me_profile-SearchPeople and the event with outlook_calendar-ListCalendarView. If either is
unclear, ask once with core-AskUserQuestion, offering the concrete candidates you found.
Derive audience emphasis from evidence, not stereotype. Read what this person has actually asked in prior threads and meetings. Only where there is no signal, fall back to role-level tendencies: operating leaders tend toward drivers and accountability; finance leaders toward accuracy and risk quantification; senior executives toward strategic framing and allocation.
2. Gather context — run these in parallel
m365_search-SearchM365withsources=["email","teams"]on the metric and period, last 14 days- The prior instance of the review — find it with
outlook_calendar-ListCalendarView, then pull its follow-up thread and any questions that were actually asked - Known sensitivities — search recent threads for concern, risk, miss, gap, or question tied to the topic
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.
- 2d ago First seen · 127 lines · 141 tokens per session scan A 09e1e440775d
stakeholder-qa-prep is a skill published in the GitHub repository microsoft/cat-agent-skills (101 stars, last pushed yesterday), licensed MIT. It adds 141 tokens to every session and 1,325 once invoked, about $0.0006 per session on Opus 5.5. 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 2026-11-06.
stakeholder-qa-prep compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| stakeholder-qa-prepmicrosoft/cat-agent-skills | Skill | 101 | yesterday | MIT | A | 141 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | yesterday | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 100k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| browser-automationopenclaw/openclaw | Skill | 394k | today | MIT | A | 36 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 314k | 4d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |