Skip to main content
skill CX Codex

figure-designer — Claude Code skill: figures for a paper

Picks the paradigm, layout and tool for the three figures that carry a paper, then audits them against a rule set.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add HKUSTDial/Supervisor-Skills --skill figure-designer -a claude-code
Open on GitHub

What figure-designer does

The skill covers the three figures that do most of the storytelling in a technical paper: the motivated example (Figure 1), the solution overview, and the experimental results plots. It first decides which type you are dealing with, then recommends a design paradigm and explains why the alternatives fit less well. What follows is a text sketch of the layout — panels, arrows, labels, colour assignments — detailed enough to draw a first draft from.

A separate pass audits the figure against universal rules: vector export format, font size of at least 8pt after scaling, a colour-blind-safe palette, a self-contained caption, honest axis ranges. Violations come back flagged by severity. Hand it an image path and it reads the file, checking font legibility, raster tells and palette directly; without an image those checks land on you.

Tool choice follows complexity. PowerPoint for a draft and Figma for polish on the motivated example and the overview, Matplotlib or Seaborn in a reusable plot_utils.py for result plots, TikZ or PGFPlots when the figure lives in LaTeX. One thing the skill cannot verify: whether the running example in Figure 1 is the same one your introduction uses. You confirm that yourself.

What it helps with

  • pick a paradigm for Figure 1 instead of guessing
  • draw a method overview that reads in under a minute
  • match the chart type to the experiment data
  • audit a finished figure for font size, palette and axis honesty
  • decide between PowerPoint, Figma, Matplotlib and TikZ

Example prompts for the agent

  • help me design Figure 1 for our method paper
  • which chart type should I use to compare four methods?
  • audit the figure at figs/overview.pdf for design violations

How to install figure-designer

1Skills CLI (Vercel)

npx skills add HKUSTDial/Supervisor-Skills --skill figure-designer -a claude-code

2Manually: put the files in place

~/.claude/skills/figure-designer/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/figure-designer/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about figure-designer

How do I install figure-designer in Claude?

Run npx skills add HKUSTDial/Supervisor-Skills --skill figure-designer -a claude-code. The skill file then sits at ~/.claude/skills/figure-designer/SKILL.md.

What does figure-designer do?

It identifies the figure type, recommends a paradigm and layout, suggests a tool, and runs a design-rule audit. It handles the motivated example, the solution overview and results plots.

Can it check a figure I already drew?

Yes, if you give it the image path: it reads the file and checks font size, palette and raster artefacts. Without an image those items are marked for you to verify.

Source text

SKILL.md · CC-BY-4.0
---
name: figure-designer
description: >-
  Advises on the design of the three core figures in a technical paper:
  the Motivated Example (Figure 1), the Solution Overview
  (Methodology), and the Experimental Results figures. Recommends the
  right design paradigm, layout, labelling, and tool for each figure
  type, then runs a quality-control audit. Use when the user asks to
  'design a figure', 'draw Figure 1', 'plot experiment results',
  'choose the right chart type', 'which figure tool to use', or
  'figure looks unprofessional'.
license: CC-BY-4.0
---

# Figure Designer

## Overview

A top-venue paper typically carries six to eight figures, with three
carrying almost all the storytelling weight: the Motivated Example
(Figure 1, on page 1 or the top of page 2), the Solution Overview
(inside the Methodology section), and the Experimental Results
figures (inside the Experiments section). Reviewers scan these three
in under a minute to decide whether the paper is worth reading in
detail; weak figures sink otherwise-strong papers.

This skill takes the user's intent (what they want to communicate)
plus context (research area, method name, target venue) and returns
the recommended paradigm, a layout sketch, labelling guidance,
tool suggestion, and a quality-control audit against a universal
rule set (vector format, font size, colour-blind-safe encoding,
self-contained caption, honest axis ranges).

## When to use this skill

- Before drawing any figure in a paper.
- The user asks to 'design a figure', 'draw Figure 1', 'plot
  experiment results', 'choose the right chart type'.
- The user has drawn a figure and wants a design audit.
- The user is unsure which figure type or paradigm to choose.
- Preparing camera-ready figures before submission.

## When NOT to use this skill

- The user only wants generic plotting help (bar chart, line chart)
  outside a paper. Regular assistance suffices.
- The paper is not yet structured; use `intro-drafter` or
  `tech-paper-template` first to decide what figures the paper
  needs.
- The user wants a review of an already-finished paper. Use
  `pre-submission-reviewer`.

## Core procedure

### Step 1: Figure-type identification

Decide which of the three core types the figure is. If the user's
request does not match any, either it is a supporting figure (use
the experimental-results guidance as a base) or it does not belong
in the paper.

If the mode is `figure-audit` and the user has provided an image
path, load the image with the Read tool **before** proceeding to
Step 2. Vision-based inspection enables the universal rule audit
in Step 6 to check font legibility, colour palette, raster-vs-
vector tells, and chartjunk directly rather than relying on user
description. If no image is provided, continue in text-only mode
and mark vision-only rules (font size, raster detection, colour
palette) as "user must verify" in the final audit report.

### Step 2: Paradigm recommendation

See: references/motivated-example.md, references/solution-overview.md,
or references/experimental-results.md depending on figure type.

Each figure type has two to three canonical paradigms. Pick the one
that fits the user's storytelling need, and explain why the other
paradigms fit less well.

### Step 3: Layout sketch

Produce a text description of the layout: panel positions, element
placement, arrows, colour assignments. The goal is that the user
could draw the first draft from the sketch alone.

### Step 4: Labelling and annotation guidance

- Name every visible element concretely (no "Module A", "X", "Y").
- Annotate critical points (failure highlight, success highlight,
  comparison emphasis).
- Specify font sizes and colour palette. Default colour palette:
  ColorBrewer Qualitative or Viridis for sequential.

### Step 5: Tool suggestion

See: references/tools.md for the tool matrix and the decision
heuristic.

Default recommendations:

- Motivated Example and Solution Overview: PowerPoint (draft),
  Figma (polish).
- Experimental Results: Matplotlib or Seaborn in a reusable
  `plot_utils.py` script.
- LaTeX-integrated figures: TikZ or PGFPlots.

### Step 6: Universal rule audit

See: references/design-rules.md for the full universal rule set.

Verify every proposed or existing figure against:

- Vector format (PDF, EPS, SVG) for export.
- Font size at least 8pt post-scaling.
- Small canvas (not large canvas with small fonts).
- Colour-blind-safe palette; no colour-only encoding.
- Self-contained caption whose first sentence states the core
  finding.
- Honest axis ranges.
- No 3D effects, no chartjunk.

Flag every violation with severity.

### Step 7: Integrity gate

Run the checks in the Integrity gate section below.

### Step 8: Output

Emit the full design in the Output format below.

## Integrity gate

Bullets tagged [inspection] are checked by the LLM from its own
output. Bullets tagged [user-verify] require the user to confirm
because the check depends on either the drawn figure or knowledge
the skill does not have (paper context, prior Introduction).

Before returning the design:

1. **[inspection]** Paradigm matches figure type (motivated example
   is not a pipeline; overview is not a bar chart).
2. **[inspection]** Layout sketch is concrete enough that the user
   could draw from it.
3. **[inspection]** Labels are real entity names, not placeholders.
4. **[inspection]** Tool suggestion matches the figure's complexity
   (not Matplotlib for a multi-icon motivated example, not
   PowerPoint for a 20-method bar chart).
5. **[inspection] when image provided, [user-verify] text-only**
   Universal rule audit has been run; no CRITICAL violation is
   left unaddressed. Vision-only rules (raster-vs-vector, font
   size, colour palette) are only checkable when the user supplies
   an image.
6. **[user-verify]** For motivated examples, the example is the
   same running example referenced by the Introduction (no new
   example introduced in Figure 1). The skill does not see the
   Introduction; the user confirms.
7. **[inspection]** For experimental results, the chart type
   matches the data type (time-series uses line, multi-method
   comparison uses grouped bar, trade-off uses scatter).

If any [inspection] check fails, mark the design as "needs user
attention". For [user-verify] items, surface them to the user as
items they must confirm before submission.

## Output format

### 1. Figure type
- Type: <motivated-example or solution-overview or experimental-results>
- Reason: <one sentence>

### 2. Paradigm recommendation
- Paradigm: <name>
- Why this paradigm: <rationale>
- Alternatives considered and rejected: <list>

### 3. Layout sketch
- Canvas: <size>
- Panels: <list with positions and contents>
- Arrows and connections: <list>
- Colour assignment: <mapping>

### 4. Labelling and annotations
- Element names: <list>
- Critical highlights: <list>
- Font sizes: <target>
- Colour palette: <name>

### 5. Tool suggestion
- Primary: <tool>
- Alternative: <tool>
- Reason: <rationale>

### 6. Universal rule audit
- [ ] Vector format: <pass or fail>
- [ ] Font size: <pass or fail>
- [ ] Colour-blind safe: <pass or fail>
- [ ] Self-contained caption: <pass or fail>
- [ ] Honest axis range (if applicable): <pass or fail>
- [ ] No chartjunk: <pass or fail>

### 7. Integrity gate result
- Gate 1-7: <pass or fail>

### 8. Severity summary
- <n> CRITICAL, <m> MAJOR, <k> MINOR
- Top three actions first: ...

© HKUSTDial · CC-BY-4.0 · HKUSTDial/Supervisor-Skills

Similar skills

Everything for Writing and docs →

From the same set12

idea-evaluator Scores a draft research idea on five dimensions, audits fatal flaws and returns a reviewer-style verdict before you sink time into the work. CX Codex +1 735installs pre-submission-reviewer Reviews a paper across five dimensions: macro logic, writing, English grammar, LaTeX and figures. Returns prioritised findings — useful in the days before a deadline. CX Codex +1 731installs intro-drafter Turns your research notes into six paragraphs of Introduction prose: limitations, goal, challenges, solution, contributions. CX Codex +1 708installs tech-paper-template Builds a complete paper logic skeleton using a thinking template and tests argument consistency before drafting begins. CX Codex +1 700installs vibe-research-workflow A skill that runs an AI-assisted research session across three sub-flows: coding, figures, writing. It picks the right tool for each stage and keeps academic judgment with you. CX Codex +1 692installs benchmark-paper-template Audits a benchmark paper against five pillars and returns a section skeleton, a six-part Introduction chain and a pre-submission checklist. CX Codex +1 679installs paper-polish Polishes an existing academic draft: grammar, flow, tone, and Chinese-to-English rewriting. The author's meaning stays intact. CX Codex +1 532installs drawio-reconstruction Reconstructs diagram images, research figures, and slides into editable .drawio files while matching the original look. It exports vector elements alongside rendered preview images. CX Codex +1 509installs

Project sponsors

Companies that keep this analytics open
Gold sponsor

Impressions, clicks and code copies — open statistics. We keep the numbers public for the same reason NeBlask itself is public. Become a sponsor