Chart Builder logo

Chart Builder

Organization
microsoft
chart-builder

Use this skill whenever the user asks to visualize, chart, plot, or graph data (bar, line, scatter, histogram, pie) from a CSV, table, or DataFrame. It gives the agent prebuilt, parameterized matplotlib functions so charts are produced faster and more reliably — with consistent styling and sane defaults — instead of hand-writing matplotlib each time.

Overview

Publishermicrosoft
Repositorycat-agent-skills
Skill namechart-builder
Stars
95
Forks
115
Bundled files
4
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by microsoft on GitHub. Read the source before you install it.

Installation

Install the Chart Builder AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/microsoft/cat-agent-skills/tree/main/submissions/chart-builder
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/microsoft/cat-agent-skills.git /tmp/cat-agent-skills
mkdir -p .claude/skills
cp -r /tmp/cat-agent-skills/submissions/chart-builder .claude/skills/chart-builder
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Chart Builder in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Chart Builder on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Chart Builder is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

  1. Provide the data source: a pandas DataFrame, or a path to a .csv / .tsv / .json file.
  2. Call the function for the chart you need, passing the column names:
    • bar(data, x, y) — one value per category (horizontal=True for barh)
    • grouped_bar(data, x, y, group) — value per category split by group (stacked=True to stack)
    • line(data, x, y, group=None) — value over an ordered axis, one line per group
    • scatter(data, x, y, group=None, size=None) — two numeric columns
    • histogram(data, y, bins=20, group=None) — distribution of one column
    • pie(data, x, y, donut=False) — share of y per category x
  3. Optional keyword args on every chart: title, xlabel, ylabel (derived from column names if omitted), out (default "chart.png"; pass None to skip saving), dpi (default 150), figsize, palette.
  4. The function returns the saved image path. See references/cheatsheet.md for full signatures and a chart-selection table.

Usage

Import:

python
from charts import bar, line, pie
bar("sales.csv", x="region", y="revenue", title="Revenue by region",
    out="revenue.png")

CLI:

bash
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 on matplotlib and pandas; 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.

Defaults

  • Colorblind-friendly palette and a shared theme across charts.
  • Figure size, x-label rotation, and legend placement adapt to the data.
  • Rows with missing values in the plotted columns are dropped before drawing.
  • Output is a saved PNG at 150 DPI by default (override out and dpi).

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Chart Builder AI skill do?

Use this skill whenever the user asks to visualize, chart, plot, or graph data (bar, line, scatter, histogram, pie) from a CSV, table, or DataFrame. It gives the agent prebuilt, parameterized matplotlib functions so charts are produced faster and more reliably — with consistent styling and sane defaults — instead of hand-writing matplotlib each time.

Why use Chart Builder on TypingMind?

Because you install it once and use it with any model. Chart Builder is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Chart Builder in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/microsoft/cat-agent-skills/tree/main/submissions/chart-builder. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Chart Builder?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Chart Builder?

As many as you like. As long as a model supports skills, you can use Chart Builder with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Chart Builder AI skill free?

Yes. It is published on GitHub by microsoft under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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