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 copilot-studio-harness-pickergit 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/copilot-studio-harness-picker)<a href="https://agentmods.dev/skills/microsoft/cat-agent-skills/copilot-studio-harness-picker"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/copilot-studio-harness-picker/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/copilot-studio-harness-picker"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/copilot-studio-harness-picker.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 | $0.00118 | $0.02642 |
| Opus 5 | $0.00059 | $0.01321 |
| Sonnet 5 | $0.00024 | $0.00528 |
| Haiku 4.5 | $0.00012 | $0.00264 |
Grade A, and why
copilot-studio-harness-picker 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 — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Copilot Studio Harness Picker
Recommend a harness only after testing hard constraints, runtime fit, channel and identity feasibility, and economics. Keep documented facts separate from assumptions and estimates.
Start the assessment
- Identify whether the user wants a conversational interview or has supplied requirements to analyze. Do not re-ask facts already provided.
- Use Quick mode by default. Use Detailed mode when requested or when the decision is high-risk, cross-tenant, externally facing, regulated, migration-heavy, or materially affected by volume and licensing.
- State the selected mode in one sentence and allow the user to switch.
- Match the explanation to the audience without weakening the analysis. Use plain, scenario-led language for makers. For architects and CoE teams, surface identity, ALM, governance, support, observability, and commercial implications explicitly.
- Read references/decision-criteria.md before forming a recommendation.
- Read references/interview-and-brief.md for the chosen interview and output format.
- Read references/credits-and-licensing.md whenever cost, licensing, capacity, build/test consumption, or M365 entitlement affects the decision.
- Read references/implementation-checks.md when channel, authentication, privileged data, approvals, files, preview maturity, observability, or a Microsoft escape route affects the design.
- Consult references/official-sources.md, and verify volatile claims against current official Microsoft documentation when web access is available. Record the date checked.
Never ask for passwords, tokens, connection strings, production records, or confidential document contents. Ask for sanitized descriptions, classifications, counts, and constraints.
Build a requirements ledger
Maintain four evidence classes throughout the assessment:
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.
- assets/credit-rates-2026-08.json 4.1 KB
- metadata.json 534 B
- README.md 4.5 KB
- references/credits-and-licensing.md 12 KB
- references/decision-criteria.md 16 KB
- references/implementation-checks.md 9.1 KB
- references/interview-and-brief.md 12 KB
- references/official-sources.md 7.8 KB
- scripts/estimate_credits.py 23 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.
- 9d ago First seen · 167 lines · 118 tokens per session scan A e977cd6724e0
copilot-studio-harness-picker is a skill published in the GitHub repository microsoft/cat-agent-skills (66 stars, last pushed 2d ago), licensed MIT. It adds 118 tokens to every session and 2,642 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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