Turn numbers into a chart — bar, line, area, pie, or doughnut. Use when asked to chart or graph data, visualize metrics/trends/breakdowns, or show numbers as a picture instead of a table. Produces a ready-to-render chart spec (renders live in the playground and exports as PNG) plus a one-line read of what the chart shows.
Scanned 9/3/2026
Install to Claude Code
npx -y skills add mohitagw15856/pm-claude-skills --skill chart --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: chart
description: "Turn numbers into a chart — bar, line, area, pie, or doughnut. Use when asked to chart or graph data, visualize metrics/trends/breakdowns, or show numbers as a picture instead of a table. Produces a ready-to-render chart spec (renders live in the playground and exports as PNG) plus a one-line read of what the chart shows."
---
# Chart Skill
A table of numbers hides the story; a chart shows it. This skill turns data into a clean, correctly-typed
chart — a **trend** as a line, a **comparison** as bars, a **composition** as a pie/doughnut — emitted as a
small JSON spec inside a ` ```chart ` block that renders live in the playground (and exports as PNG).
## Required Inputs
Ask for these only if they aren't already provided:
- **The data** — the numbers, with their labels/categories (paste a table, list, or metrics).
- **What you want to show** — a trend over time, a comparison between things, or parts of a whole. This decides the chart type.
- **Series** — one metric or several (e.g. revenue *and* churn over the same months).
- **Title** (optional) — what the chart is about.
If the data implies the wrong chart type for the goal, pick the right type and say why.
## Output Format
### [What the chart shows]
A one-line read — the takeaway the chart makes obvious.
```chart
{
"type": "line",
"title": "MRR vs. churned MRR (2026)",
"labels": ["Jan", "Feb", "Mar", "Apr", "May", "Jun"],
"series": [
{ "name": "MRR ($k)", "data": [120, 138, 151, 167, 180, 201] },
{ "name": "Churned ($k)", "data": [8, 9, 7, 11, 9, 8] }
]
}
```
**Notes** (optional) — caveats, the source of the numbers, or what a follow-up chart would show.
## Chart Spec Rules (so it renders)
- Emit a single ` ```chart ` block containing **valid JSON** (double-quoted keys/strings, no trailing commas, no comments).
- `type`: `"bar"`, `"line"`, `"area"`, `"pie"`, or `"doughnut"`.
- `labels`: the x-axis categories (or the slice names for pie/doughnut).
- `series`: an array of `{ "name": "...", "data": [numbers] }`. Pie/doughnut uses the first series only.
- Every series' `data` length must match `labels` length. Numbers only — no units inside the array (put units in the series name or title).
- **Choose the type by intent:** trend over time → line/area; compare categories → bar; parts of a whole → pie/doughnut.
## Quality Checks
- [ ] Chart type matches the intent (trend → line, comparison → bar, composition → pie)
- [ ] The JSON is valid and renders without edits (no trailing commas, all strings quoted)
- [ ] Every series' data length equals the number of labels
- [ ] Units/scale are clear (in the title or series names), and the one-line read states the takeaway
- [ ] Multiple series are used only when they share the same axis/scale
## Anti-Patterns
- [ ] Do not use a pie chart for more than ~6 slices or for trends — pies show composition, not change
- [ ] Do not put units or text inside the numeric `data` array — it breaks the chart
- [ ] Do not emit invalid JSON (trailing commas, single quotes, comments) — it won't render
- [ ] Do not mismatch lengths — a series shorter/longer than the labels misaligns the chart
- [ ] Do not chart numbers you weren't given — flag gaps instead of inventing data points
## Based On
Data-visualization practice (chart-type-to-intent: trend/comparison/composition), emitted as a renderable chart spec.
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