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 generating-podcast-scriptgit 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/generating-podcast-script)<a href="https://agentmods.dev/skills/microsoft/cat-agent-skills/generating-podcast-script"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/generating-podcast-script/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/generating-podcast-script"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/generating-podcast-script.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 | $0.00089 | $0.02654 |
| Opus 5.5 | $0.00036 | $0.01062 |
| Sonnet 5.5 | $0.00018 | $0.00531 |
| Haiku 4.5 | $0.00009 | $0.00265 |
Grade A, and why
generating-podcast-script 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 1mo 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 — 237 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Podcast Script Generation
Produces a two-host, NotebookLM-style conversational episode: a readable script plus a multi-voice SSML document ready for Azure Text-to-Speech.
Step 1 — Gather inputs
Ask only for what is missing. Do not ask for optional fields that have safe defaults.
| Input | Required | Default |
|---|---|---|
source or topic |
Yes | — (source material such as a digest/newsletter/articles, or a plain topic) |
duration |
No | medium — short ≈ 3 min / ~450 words, medium ≈ 6 min / ~900 words, long ≈ 12 min / ~1,800 words |
language |
No | English |
cast |
No | Two hosts, NOVA and MILES (see Step 4) |
generate_audio |
No | Ask after the script is ready |
All word targets assume ~150 spoken words per minute. Stay within 10 percent of target.
Derive a lowercase-hyphenated <slug> from the source or topic (max 6 words,
ASCII only).
Step 2 — Parse the source material
Skip this step when the user gave a bare topic with no source material.
Extract every distinct article or item. For each, capture:
- headline
- publication / source
- date, if present
- the core factual claim
- any figures or quotes
- the "so what"
Merge duplicates covering the same event. Discard boilerplate, footers, disclaimers, legal notices, unsubscribe text, and image captions.
Step 3 — Editorial selection
Rank items by newsworthiness and reader impact. Keep the top 4 to 6 for full
treatment (fewer for short, more for long). Group the remainder into one
fast rapid fire segment. If the material has a dominant theme, lead with it
and thread it through the episode.
Step 4 — Cast
Two hosts, always the same personalities, always distinct voices:
- NOVA — voice
en-US-AvaMultilingualNeural. Lead host. Warm, curious, quick. Drives the agenda, asks the question the listener is thinking, reacts out loud, reframes jargon into plain language. Slightly faster cadence. - MILES — voice
en-US-AndrewMultilingualNeural. Analyst. Calm, dry, precise. Supplies context, numbers, caveats, second-order implications. Slightly slower, lower pitch. Occasionally pushes back on Nova.
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.
- 1mo ago First seen · 237 lines · 89 tokens per session scan A cb59026214ee
generating-podcast-script is a skill published in the GitHub repository microsoft/cat-agent-skills (93 stars, last pushed today), licensed MIT. It adds 89 tokens to every session and 2,654 once invoked, about $0.0004 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 2026-08-30.
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