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 style-analyzergit 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/style-analyzer)<a href="https://agentmods.dev/skills/microsoft/cat-agent-skills/style-analyzer"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/style-analyzer.svg" alt="Measured on agentmods" 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 | $0.00079 | $0.00951 |
| Opus 5 | $0.00039 | $0.00476 |
| Sonnet 5 | $0.00016 | $0.00190 |
| Haiku 4.5 | $0.00008 | $0.00095 |
Grade A, and why
style-analyzer 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 3d 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 — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Style Analyzer
Analyze the user's communication patterns across Teams and Outlook and build a style profile that other skills or automations (e.g. an out-of-office auto-responder) can use to write in the user's voice. Save the profile to memory so it's available across sessions.
Tool names. This skill refers to Microsoft 365 tools as
m365_*and to memory as remember/recall tools. If your host exposes these under different names, map them to the equivalent capability.
Data collection
1. Gather sent emails (20–30 samples)
- List the last ~30 emails in the Sent folder.
- For emails with real body content (not just meeting accepts/declines), fetch the full text body.
2. Gather Teams chat messages
- List recent chats (~50).
- For each relevant chat (prioritize active 1:1 and group chats), fetch the last ~30 messages.
- Filter to messages from the current user (match the
fromfield to the user's display name).
3. Sample diversity
Aim for:
- 10+ sent emails with body content
- 50+ Teams messages across 20–25 different chats
- A mix of 1:1, group, and meeting chats
- Both internal and external conversations where available
Analysis framework
Analyze the collected messages across these dimensions:
- A. Greetings — how they address people (first name, "Hi [Name]", "Hey", formal titles); patterns by relationship type (internal vs external).
- B. Tone & formality — professional/casual/mixed; direct vs hedging; warmth indicators.
- C. Message length — average sentence count; frequency of one-word replies; when they write longer messages.
- D. Punctuation & grammar — consistency; common typos (e.g. lowercase "i"); emoji usage (none / occasional / frequent).
- E. Sign-offs — email signature style; Teams message endings; closing phrases ("Thanks", "Regards", etc.).
- F. Common phrases — frequently used expressions for agreement ("sounds good", "makes sense"), requests ("can you", "would you mind"), availability, and FYI/context-setting.
- G. Technical communication — how they explain technical concepts; level of detail; hedging vs confidence.
- H. Action patterns — how they delegate, loop others in, and schedule meetings.
What ships with it
2 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.
- 3d ago First seen · 121 lines · 79 tokens per session scan A 9a6f6f6b54df
style-analyzer is a skill published in the GitHub repository microsoft/cat-agent-skills (64 stars, last pushed yesterday), licensed MIT. It adds 79 tokens to every session and 951 once invoked, about $0.0004 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 2026-09-03.
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