Figure Qa

Community

neuromechanist

figure-qa

Use this skill to QA a scientific figure for journal compliance, alignment, palette correctness, and text legibility. Triggers on "QA this figure", "check this figure", "review my figure", "is this figure paper-ready", "validate figure", "check the text in this figure", or when invoked after a figures skill produces output (unless the caller passes no-qa). Dispatches on input type (SVG, raster PNG/JPG/TIFF, Python plot script, or composed-figure directory), runs the programmatic checks including OCR of expected strings and palette compliance against the project theme, adds a vision rubric pass, and returns a report with a machine-readable JSON verdict that drives the generate, QA, fix loop.

Overview

Publisher	neuromechanist
Repository	`research-skills`
Skill name	`figure-qa`
Stars	51
Forks	9
Bundled files	2
License	BSD-3-Clause
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
2 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by neuromechanist on GitHub. Read the source before you install it.

Installation

Install the Figure Qa AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/neuromechanist/research-skills/tree/main/plugins/figures/skills/figure-qa
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/neuromechanist/research-skills/tree/main/plugins/figures/skills/figure-qa

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/neuromechanist/research-skills.git /tmp/research-skills
mkdir -p .claude/skills
cp -r /tmp/research-skills/plugins/figures/skills/figure-qa .claude/skills/figure-qa

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Figure Qa in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Figure Qa on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Figure Qa is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Figure QA

Routes a scientific figure to an independent, fresh-context QA reviewer that detects the input type, runs the deterministic checks (fonts, palette, geometry, alpha, resolution, rendered text) with the helper scripts, and adds a vision-language model (VLM) rubric judgment for the aesthetic dimensions. This skill is a thin dispatcher: the detection logic, exit-code contract, VLM rubric, report shape, and the iterate loop all live in references/, and the deterministic engine lives in the figures plugin's agents/figure-qa-scripts/.

When to use

Activate when a figure needs a journal-submission QA pass, or after a figures skill (figures:scientific-figure, figures:svg-figure, figures:svg-primitives, figures:transparent-icons, figures:ai-full-figure, figures:plot-styling) produces output, unless the caller passes no-qa.

What to pass to the reviewer

Every dispatch carries the same briefing, so the right checks run:

the figure path and, when known, the input type
the target journal (nature, science, cell, pnas, poster, slide, or generic)
the theme path (figures/theme.json) so palette compliance is judged against the project bible rather than a fixed allow-list
every verbatim string the figure was asked to render (titles, panel letters, labels); without this list the raster text check is silently off
the physical width in millimetres for raster inputs, so text height converts to points

Why a fresh-context reviewer

A QA pass is more trustworthy from a reviewer that did not just author the figure. Run it in a separate context and pass only the briefing above. On tools without subagents, run the procedure inline. For several candidates, issue one dispatch per candidate in a single message so they run in parallel on the Sonnet tier.

Dispatch

In every branch the reviewer follows references/figure-qa-procedure.md (strict separation: scripts own ground-truth measurements, the VLM owns aesthetic judgment).

Claude Code: Agent(subagent_type: "figures:figure-qa", ...) with the briefing above. Honor a no-qa opt-out by returning immediately.
Codex CLI: plugin installation exposes this skill, not a Codex subagent. To use a fresh-context Codex reviewer, first copy ${CLAUDE_PLUGIN_ROOT}/agents/templates/figure-qa.toml (the plugin's agents/templates/ directory) to ~/.codex/agents/ or .codex/agents/, then invoke that configured agent if the current Codex surface supports /agent. If no Codex subagent is configured or available, use the fallback branch.
Copilot CLI: plugin installation exposes this skill and, through .github/plugin/plugin.json, the .agent.md reviewer in agents/templates/. Invoke that configured agent when the current Copilot surface supports custom agents. If running outside a plugin install, copy agents/templates/figure-qa.agent.md to .github/agents/ or ~/.copilot/agents/. If no custom agent is available, use the fallback branch.
Fallback (no subagent support, or an interactive in-thread check): first locate the procedure ($CLAUDE_PLUGIN_ROOT/skills/figure-qa/references, else find . -type d -path '*/skills/figure-qa/references' | head -1); if it cannot be found, stop and tell the user to install the figures plugin rather than guessing checks. Then follow references/figure-qa-procedure.md directly.

The report and the loop

The report keeps its markdown sections and ends with one fenced JSON block: status (ship, revise, block), findings[] each with check, severity, message, action (regenerate, edit, overlay, rescale, recolor, none) and a hint, plus measurements and the five VLM scores. Generation skills branch on that block. references/iterate-loop.md defines the generate, QA, fix, regenerate loop (N candidates in parallel, one targeted change per iteration, stop at ship or after three iterations) that figures:ai-full-figure follows.

The brain (do not duplicate into dispatch or agent shells)

references/figure-qa-procedure.md: no-qa opt-out, script location, type detection, per-branch checks including the raster text check and theme palette compliance, exit-code contract, VLM rubric, the exact report shape, and the finding-to-action table.
references/iterate-loop.md: the candidate, QA, fix loop with its worker briefing and stopping conditions.
agents/figure-qa-scripts/check_{svg,raster,plot_script}.py (in the figures plugin): the deterministic engine, kept in place so other skills can call it directly. check_raster.py --json --expect-text "..." --palette figures/theme.json --width-mm 89 --journal nature is the text and palette check; check_svg.py --json --palette figures/theme.json covers SVG geometry, fonts, and palette.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Figure Qa AI skill do?

Why use Figure Qa on TypingMind?

Because you install it once and use it with any model. Figure Qa is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Figure Qa in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/neuromechanist/research-skills/tree/main/plugins/figures/skills/figure-qa. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Figure Qa?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Figure Qa?

As many as you like. As long as a model supports skills, you can use Figure Qa with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Figure Qa AI skill free?

Yes. It is published on GitHub by neuromechanist under the BSD-3-Clause license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Figure QA

When to use

What to pass to the reviewer

Why a fresh-context reviewer

Dispatch

The report and the loop

The brain (do not duplicate into dispatch or agent shells)

Bundled files

Frequently asked questions

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