graphing Skill
Compose polished charts (timeseries, bar, line, area, pie, scatter, or anything else the data calls for) from tabular data using the chartkit primitives, producing PNG, SVG, or self-contained interactive HTML. Use when the user asks to chart, graph, plot, or visualize data and wants something better than raw matplotlib Published by anthropics in claude-tag-plugins.
What is graphing Skill?
Compose polished charts (timeseries, bar, line, area, pie, scatter, or anything else the data calls for) from tabular data using the chartkit primitives, producing PNG, SVG, or self-contained interactive HTML. Use when the user asks to chart, graph, plot, or visualize data and wants something better than raw matplotlib Published by anthropics in claude-tag-plugins. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Data analysis
- Writing
- Data analysis use cases
- Writing use cases
Technical details
- Install or run with Copy skill directory
When to use graphing Skill
- Use it for data analysis.
- Use it for writing.
Built with
Editorial notes
Source
- Creator: anthropics
- Repository: anthropics/claude-tag-plugins
- Skill file: claude-tag-data-viz/skills/graphing/SKILL.md
What it does
Compose polished charts (timeseries, bar, line, area, pie, scatter, or anything else the data calls for) from tabular data using the chartkit primitives, producing PNG, SVG, or self-contained interactive HTML. Use when the user asks to chart, graph, plot, or visualize data and wants something better than raw matplotlib
Skill instructions
Graphing You write the plotting code. The kit provides the parts that should stay consistent across every chart: typography, color derivation from the background, the title and caption frame, and offline HTML packaging. Everything about the chart itself is your judgement applied to the data in front of you. The primitives Import chartkit by putting this skill's scripts/ directory on sys.path. Use its absolute path, not a relative path, since your working directory is the user's project. The examples below write it as /path/to/graphing/scripts; substitute the real path. Relevant primitives: - theme(bg, font): sets matplotlib rcParams and returns resolved colors. Foreground colors derive from background luminance, so a dark bg produces a correct dark chart. Fields: bg dark text muted grid spine accent secondary series fontcss. - palette(n, base): n colors. No base cycles the default series, a hex base builds a ramp from it, a list cycles the list. - finish(ax, title, subtitle, source): T
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Frequently asked questions
What is graphing?
graphing is a open-source AI agent skill with Copy skill directory. Compose polished charts (timeseries, bar, line, area, pie, scatter, or anything else the data calls for) from tabular data using the chartkit primitives, producing PNG, SVG, or self-contained interactive HTML.
Who is graphing best for?
graphing is best for reusing agent instructions, scripts, and references, data analysis workflows, writing workflows.
How do I install graphing?
Install or run graphing using Copy skill directory. Check graphing for the latest setup command.
Is graphing actively maintained?
graphing may need a closer maintenance check before production use.
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