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 chart-buildergit 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/chart-builder)<a href="https://agentmods.dev/skills/microsoft/cat-agent-skills/chart-builder"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/chart-builder/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/chart-builder"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/chart-builder.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 | $0.00076 | $0.00714 |
| Opus 5.5 | $0.00030 | $0.00286 |
| Sonnet 5.5 | $0.00015 | $0.00143 |
| Haiku 4.5 | $0.00008 | $0.00071 |
Grade A, and why
chart-builder 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 — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate charts from tabular data via the bundled scripts/charts.py toolkit.
Each function takes a DataFrame or a file path plus the columns to plot, and
saves a PNG (returning the path). It handles theming, figure sizing, label
rotation, NaN dropping, legend placement, and saving.
Instructions
- Provide the data source: a pandas DataFrame, or a path to a
.csv/.tsv/.jsonfile. - Call the function for the chart you need, passing the column names:
bar(data, x, y)— one value per category (horizontal=Truefor barh)grouped_bar(data, x, y, group)— value per category split bygroup(stacked=Trueto stack)line(data, x, y, group=None)— value over an ordered axis, one line pergroupscatter(data, x, y, group=None, size=None)— two numeric columnshistogram(data, y, bins=20, group=None)— distribution of one columnpie(data, x, y, donut=False)— share ofyper categoryx
- Optional keyword args on every chart:
title,xlabel,ylabel(derived from column names if omitted),out(default"chart.png"; passNoneto skip saving),dpi(default150),figsize,palette. - The function returns the saved image path. See
references/cheatsheet.mdfor full signatures and a chart-selection table.
Usage
Import:
from charts import bar, line, pie
bar("sales.csv", x="region", y="revenue", title="Revenue by region",
out="revenue.png")
CLI:
python scripts/charts.py grouped_bar sales.csv \
--x region --y revenue --group quarter --stacked --out by_quarter.png
Bundled files
scripts/charts.py— the toolkit:load_data,apply_theme,save_fig, and six chart functions (bar,grouped_bar,line,scatter,histogram,pie), plus a CLI. Depends onmatplotlibandpandas; runs headless.references/cheatsheet.md— chart-selection table, full signatures, and copy-paste CLI examples.assets/sample_sales.csv— a small demo dataset that exercises every chart.
What ships with it
5 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 · 56 lines · 76 tokens per session scan A 802381b192ce
chart-builder is a skill published in the GitHub repository microsoft/cat-agent-skills (93 stars, last pushed today), licensed MIT. It adds 76 tokens to every session and 714 once invoked, about $0.0003 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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