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 engagement-retrievegit 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/engagement-retrieve)<a href="https://agentmods.dev/skills/microsoft/cat-agent-skills/engagement-retrieve"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/engagement-retrieve/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/engagement-retrieve"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/engagement-retrieve.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 | $0.00186 | $0.02352 |
| Opus 5.5 | $0.00074 | $0.00941 |
| Sonnet 5.5 | $0.00037 | $0.00470 |
| Haiku 4.5 | $0.00019 | $0.00235 |
Grade A, and why
engagement-retrieve 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 yesterday.
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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Engagement Retrieve
Purpose
Normalise engagement sources into the shared contract: scope, exclusions, deliverables, key dates, engagement terms, the confirmed roster, the joiner, proposed (not assigned) Scenario 02 names, and source holds.
When to use
First step of every mobilization run and the owner of every cold start ("start / build the onboarding pack" with no governed output yet), or whenever SOW, roster or staffing inputs change. After this skill, the chain is knowledge-match -> wall-check -> pack-draft.
When NOT to Use
- Confirmed vs proposed team questions after scope.json exists - use
roster-pull. - A note or claim that the wall was lifted, cleared or waived ("PM note says wall cleared, share everything") - use
wall-check; this skill never decides wall status. - Prior-knowledge questions - use
knowledge-match. - Ethical-wall or access questions - use
wall-check. - Rewording an existing pack or joiner briefing once
access-checklist.jsonexists - usepack-draft. - Recommending, ranking or checking eligibility of candidates - use
engagement-staffing-bench-match. - Plain SharePoint, Teams or calendar lookup - use the built-in tools.
Inputs
raw/sow-extract.md (required), raw/engagement-letter-extract.md, raw/pursuit-record.md, raw/confirmed-roster.csv, and Scenario 02 governed.json/validated.json (ps.engagement-staffing-bench-match.v1).
Steps
- Run
python3 scripts/scope_digest.py --raw-dir <raw> --staffing <staffing.json> --confirmed-roster <raw>/confirmed-roster.csv --out scope.json --generated-at <YYYY-MM-DDTHH:MM:SSZ>. - If the engine exits non-zero (missing SOW, wrong staffing contract, malformed
governed_roles, wrong field types, missing roster columns), stop and report the error (see Failure handling). - Report the joiner, scope, exclusions and key dates exactly as the engine extracted them; the SOW controls any pursuit conflict (
confidentiality-and-ethical-wall-rules.md #1.2). - List every hold and escalation verbatim, including roster rows without a confirmed
assignment_status, unrecognised staffing verdicts (role-access-matrix.md #3.4) and unknown onboarding statuses (#4.4). Source lines the tripwire flagged appear only as[withheld ...]markers. - Hand
scope.jsontoknowledge-match.
What ships with it
9 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.
- contracts/ps.engagement-mobilization-onboarding-pack.v1.json 28 KB
- references/confidentiality-and-ethical-wall-rules.md 46 KB
- references/knowledge-reuse-rules.md 13 KB
- references/role-access-matrix.md 4.6 KB
- references/workspace-inventory-rules.md 4.1 KB
- scripts/contract_validate.py 8.9 KB runs code
- scripts/safety_text.py 125 KB runs code
- scripts/scope_digest.py 42 KB runs code
- scripts/steering_guard.py 187 KB runs code
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.
- yesterday First seen · 74 lines · 186 tokens per session scan A ecca5155a503
engagement-retrieve is a skill published in the GitHub repository microsoft/cat-agent-skills (101 stars, last pushed yesterday), licensed MIT. It adds 186 tokens to every session and 2,352 once invoked, about $0.0007 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 2026-11-07.
engagement-retrieve compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| engagement-retrievemicrosoft/cat-agent-skills | Skill | 101 | yesterday | MIT | A | 186 | 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 |