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 improve-legal-promptgit 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/improve-legal-prompt)<a href="https://agentmods.dev/skills/microsoft/cat-agent-skills/improve-legal-prompt"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/improve-legal-prompt/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/improve-legal-prompt"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/improve-legal-prompt.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 | $0.00168 | $0.02552 |
| Opus 5.5 | $0.00067 | $0.01021 |
| Sonnet 5.5 | $0.00034 | $0.00510 |
| Haiku 4.5 | $0.00017 | $0.00255 |
Grade A, and why
improve-legal-prompt 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 — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Improve legal prompt
Convert the user's rough request or existing prompt into one ready-to-use prompt for Cowork. Preserve the original objective while clarifying the intended legal outcome, document scope, constraints, required inputs, handling of missing information, and expected response format.
This skill optimizes the prompt. It does not perform the legal analysis, review, drafting or editing the prompt describes, and it never guarantees a legal outcome.
When NOT to Use
Use this skill only when the user explicitly asks to create, improve, clarify, diagnose or rewrite a prompt, instruction or request for Cowork.
Rewrite my prompt for reviewing this agreement— prompt optimization. In scope.How should I ask Cowork to revise the termination clause?— prompt optimization. In scope.Rewrite this clause,make this paragraph clearer,improve the termination provision— document editing. Useedit-contract.Is this clause enforceable?,what does this mean for us?— uselegal-reasoning, orexplain-legal-conceptsfor a plain language explanation.Review this agreement— usereview-contract.- A vague legal request does not become a prompt-optimization request merely because a better prompt might improve the result.
Hand-off rule. If a request, or part of one, matches an item above that names
another skill, do not do that part here — even when the documents are already open
and the work looks quick. Name the skill that handles it (for example, "That part
is a job for edit-contract") and stop that part; finish only what belongs to
this skill. If the named skill is not installed, say so plainly and do not attempt
it here.
Step 1: Identify the source request
- Treat text the user pastes, quotes, labels as a prompt, or describes as their instruction as the source.
- Where the turn refers to a prompt from the recent conversation, use the most recent unambiguous prompt under discussion.
- If the user gives a target task but no draft prompt, write the prompt from scratch.
- If neither a source prompt nor a target task is identifiable, ask exactly:
What prompt would you like me to optimize? - Preserve exact values, defined labels, clause numbers, field names, schemas, allowed values, word limits, exceptions and formatting requirements unless the user asks to change them. Never carry a personal identifier through into the optimized prompt: an optimized prompt is re-run downstream, so a national insurance or social security number, bank or payment card detail, home address, date of birth, salary or health datum copied out of the source request or a supplied document propagates into every later run. Replace it with a role or a neutral placeholder, keep the instruction intact, and say what you replaced and why; where the source prompt asks for such a field as an output, drop that field from the optimized prompt and say so. See Personal data minimisation in Guardrails.
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 · 225 lines · 168 tokens per session scan A 7cc26c88139c
improve-legal-prompt is a skill published in the GitHub repository microsoft/cat-agent-skills (101 stars, last pushed yesterday), licensed MIT. It adds 168 tokens to every session and 2,552 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 2026-11-06.
improve-legal-prompt compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| improve-legal-promptmicrosoft/cat-agent-skills | Skill | 101 | yesterday | MIT | A | 168 | Claude Code, Codex |
| fto-triageanthropics/claude-for-legal | Skill | 9.9k | yesterday | Apache-2.0 | A | 81 | Claude Code |
| legal-holdanthropics/claude-for-legal | Skill | 9.9k | yesterday | Apache-2.0 | A | 68 | Claude Code |
| specification-writingwanshuiyin/Auto-claude-code-research-in-sleep | Skill | 19k | today | MIT | A | 49 | Claude Code |
| regulatory-research-fallbackHKUDS/OpenSpace | Skill | 7.9k | 2d ago | MIT | A | 20 | Claude Code, Codex |
| terms-of-servicegenspark-ai/genoffice | Skill | 12k | today | Apache-2.0 | A | 32 | Claude Code, Codex |
| x-scorecardx-cmd/x-cmd | Skill | 4.7k | 8d ago | Apache-2.0 | A | 57 | Claude Code, Codex |