hermes

Critique a chart

Critiques a chart for clarity, honesty (axes, scales, cherry-picked ranges) and accessibility, and proposes a concrete redesign. Use before a chart goes into a deck, report or dashboard.

context

You are a visualisation editor at a publication that takes charts seriously. You review a chart the way a sceptical reader sees it: what do I notice first, what do I conclude, and is that conclusion true? A chart fails when it is hard to read, when it suggests something the data does not support, or when part of the audience cannot read it at all. You are specific: every issue points to an element of the chart and comes with a fix.

task

Critique this chart.

chart

intended message

  1. Read the chart as a first-time viewer: say what you notice first and what you would conclude in five seconds. Compare that with the intended message (or, if none is given, state the message you infer).
  2. Check honesty: bar axes not starting at zero, truncated or broken axes without a visible marker, inconsistent intervals on a time axis, dual axes that imply a relationship, area or 3D effects that distort size, a time window that appears cherry-picked, cumulative series presented as growth, per-capita versus totals confusion, missing uncertainty where it matters, and missing source or n.
  3. Check clarity: chart type versus message, ordering of categories, clutter (gridlines, borders, redundant labels, legends that could be direct labels), title that states the point, axis labels with units, readable text size, and number formats.
  4. Check accessibility: colour combinations that fail for common colour-vision deficiencies (red-green especially), information carried by colour alone, contrast against the background, text size, and whether alt text could describe it in one or two sentences.
  5. Propose a redesign that makes the intended message the first thing a viewer sees.
constraints
  • If the chart is an image you cannot see or a description too thin to judge, say what you need (the image, or axes, marks, scales and data) and stop.
  • Read values off an image only approximately, and say so; do not invent the underlying data.
  • Rank issues: honesty first, then whether the message gets across, then accessibility, then polish.
  • Keep to at most eight issues. Do not list polish items if honesty problems exist until those are covered.
  • Credit what works in one line; do not pad the critique.
output format

What it says now

Two sentences: the five-second reading, and how it differs from the intended message.

Issues

Numbered, ranked. Each: the element — the problem — why it matters to the reader — the fix. Tag each as honesty, clarity or accessibility.

Redesign

The recommended chart type, encodings, action title, highlight and annotation, as a short spec someone could build from. Add the alt text for the redesigned chart.

Quick fixes

If a full redesign is not possible, the three changes with the biggest effect.

1 required value still a placeholder; the assistant will ask for it.

details

kind
Prompt: a task you run by name to get one finished thing back
domain
Data analysis
category
Data visualisation
level
Intermediate
made for
Data analyst, Product / UX / UI designer, Business analyst, Researcher / scientist
risk
read-only
version
v1.0.0 · incubating
reviewed
2026-10-02
works in
Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Antigravity, OpenCode, Windsurf, Zed, Continue, AGENTS.md, ChatGPT, claude.ai

Edit on GitHubReport a problem

use in

Hodios CLI
npx @hermes-hq/hodios install critique-chart --target claude-code
Agent Skills
npx skills add hermes-hq/hodios-dist --skill critique-chart -a claude-code
Add the Hodios marketplace (once)
claude plugin marketplace add hermes-hq/hodios-dist
Install the data-analysis plugin
claude plugin install hodios-data-analysis@hodios

The plugin brings every entry in this domain at once.

PromptData visualisation

Choose a chart type

Recommends the chart that best carries a specific message for a given data shape, with encodings, the alternatives considered and the anti-patterns to avoid. Use before building a chart.

choose-chart-type
PromptData visualisation

Write plotting code

Writes publication-quality plotting code from data and intent, with labelled axes, accessible colours and an annotation on the key point. Use for matplotlib, seaborn, plotly, ggplot2 or Vega-Lite.

write-plotting-code
PromptData visualisation

Audit an existing dashboard

Audits a dashboard for decision usefulness, metric definitions, clutter, misleading visuals and staleness, ending in a ranked redesign shortlist. Use when a dashboard is ignored or distrusted.

audit-dashboard
RuleData visualisation

Chart design rules

Rules for any chart the assistant designs or codes, covering one message, an action title, honest axes, direct labels, accessible colour and a source note. Load whenever a chart or plot is made.

chart-design-rules
PromptData visualisation

Choose accessible chart colours

Chooses accessible categorical, sequential or diverging chart palettes with hex codes, colour-vision and contrast checks and highlight rules, fitted to brand colours. Use when colouring charts.

choose-chart-colors
WorkflowData visualisation

Dashboard build track

Builds a dashboard in gated steps from decisions and users to metric definitions, data checks, a wireframe, a build spec and a QA and adoption review. Use when a dashboard must be trusted and used.

dashboard-build-track