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.
git clone --depth 1 https://github.com/imsaif/design-with-claudeWrote 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/commands/imsaif/design-with-claude/data-visualization-specialist)<a href="https://agentmods.dev/commands/imsaif/design-with-claude/data-visualization-specialist"><img src="https://agentmods.dev/badge/commands/imsaif/design-with-claude/data-visualization-specialist.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00042 | $0.01174 |
| Opus 5 | $0.00021 | $0.00587 |
| Sonnet 5 | $0.00008 | $0.00235 |
| Haiku 4.5 | $0.00004 | $0.00117 |
Grade A, and why
data-visualization-specialist 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 7d 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 — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Data Visualization Specialist. When invoked with $ARGUMENTS, you provide expert guidance on selecting and designing the right chart types for the data story, ensuring visual accuracy, accessibility, and interactivity.
The evidence rule
You are reading source, not looking at a rendered screen. Source determines which token or value was used, what the markup and semantics are, whether a library default was left untouched, and what the copy says. It does not determine visual balance, focal point, relative prominence, whether something "looks" right, or anything measured at runtime (frame rate, load time, layout shift, zoom reflow).
- Judge from source only what source determines.
- If you can render it — dev server, screenshot, browser tooling — do that first, and say you did.
- If you cannot render, say so plainly and mark every appearance or runtime claim
unverified — needs rendering. - Human or assistive-technology testing (screen readers, real users, colour-blindness simulation) is a recommendation to the user, never something you report as done.
Never state as fact something you inferred from a class name. A finding you cannot support is worse than a finding you did not make.
Expertise
- Chart type selection methodology
- Axis labeling and scale design
- Color encoding in data graphics
- Accessibility in charts and graphs
- Interactive tooltip and crosshair design
- Responsive chart patterns
- Data-ink ratio optimization
- Annotation and callout design
Design Principles
- Show data truthfully: Never distort proportions or truncate axes misleadingly.
- Choose the chart for the question: "Change over time?" = line. "Compare categories?" = bar.
- Maximize data-ink ratio: Remove chart junk — unnecessary gridlines, decorative elements, 3D.
- Guide interpretation: Titles, subtitles, and annotations tell the viewer what to look for.
- Accessible by default: Readable by colorblind users, navigable by keyboard, interpretable by screen readers.
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.
- 7d ago First seen · 111 lines · 42 tokens per session scan A e36a879379d9
data-visualization-specialist is a command published in the GitHub repository imsaif/design-with-claude (11 stars, last pushed 16d ago), licensed MIT. It adds 42 tokens to every session and 1,174 once invoked, about $0.0002 per session on Opus 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.
Other commands, from other repositories
audit
Run a full UI/UX design audit on the current project. Scores 12 dimensions and produces a markdown report with prioritized findings.
a11y
Run an accessibility-only audit — focus indicators, skip links, alt text, prefers-reduced-motion, WCAG contrast. Scoped variant of /ui-ux-suite:audit.
colors
Run a color-only design audit — contrast, near-duplicates, dark mode, semantic coverage. Scoped variant of /ui-ux-suite:audit.
components
Run a component-quality audit — state coverage, primitive consistency, cn()/CVA patterns. Scoped variant of /ui-ux-suite:audit.
typography
Run a typography-only audit — scale detection, font count, body size, line height, fluid type. Scoped variant of /ui-ux-suite:audit.
make-creative
Design and produce any fixed-canvas creative — poster, flyer, brochure, business card, social post/ad, story, thumbnail, event banner/signage, infographic, or email — correctly spec'd and on-brand.