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.
npx skills add xuzhougeng/ScientificFigureLibrary --skill figure-stylegit clone --depth 1 https://github.com/xuzhougeng/ScientificFigureLibraryWrote 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/skills/xuzhougeng/scientificfigurelibrary/figure-style)<a href="https://agentmods.dev/skills/xuzhougeng/scientificfigurelibrary/figure-style"><img src="https://agentmods.dev/badge/skills/xuzhougeng/scientificfigurelibrary/figure-style/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/xuzhougeng/scientificfigurelibrary/figure-style"><img src="https://agentmods.dev/badge/skills/xuzhougeng/scientificfigurelibrary/figure-style.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00057 | $0.00585 |
| Opus 5 | $0.00028 | $0.00293 |
| Sonnet 5 | $0.00011 | $0.00117 |
| Haiku 4.5 | $0.00006 | $0.00059 |
Grade A, and why
figure-style 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 5d 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 — 37 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Figure Style — faithful template first
This SFL-bundled entrypoint adapts Wisp Science's Apache-2.0 figure-style guidance. See LICENSE and NOTICE.md for the attribution and adaptation record.
Use this plugin's Skill rather than a Host copy. Follow the user's selected backend and project runtime approvals. A local R-only project rule does not prohibit Python in other projects.
Priority
- Data and semantic truth: labels, thresholds, colour mappings and summaries must agree with the actual data and analysis.
- The user's explicit current requirements.
- The selected template's layout, palette, font, legend, axes and visual identity.
- General style defaults only where the reference/user does not specify an answer.
Do not silently replace a palette, font, chart type, legend, grid or layout to comply with a generic aesthetic preference. Where the reference has low contrast, overlaps or inconsistent labels, explain the issue and propose a change; do not conceal the defect or call a restyled version a faithful reproduction. Never alter data to make a preferred shape. Plotting a synthetic scaffold is not reproducing the original experiment.
Backend routing
- For R/ggplot2/base graphics read R guidance. R never requires the Python kernel.
- For Python/matplotlib read Python guidance. The bundled kernel is optional and local; its absence in the Host's global skills is irrelevant.
- For other backends apply the correctness checks without switching language or claiming an unsupported automated QA check passed.
Read correctness and render checks before finalizing the output. This Skill does not depend on figure-composer or paper-narrative; multi-panel work stays within the requested figure boundary.
Execution and output
Materialization downloads/verifies/writes references; it does not authorize arbitrary code execution. Inspect sources before adapting them, use only the project's approved runtime, never install packages automatically, and keep references immutable. Write adapted project code under figure-organization.
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago First seen · 37 lines · 57 tokens per session scan A a2e36d30ef18
figure-style is a skill published in the GitHub repository xuzhougeng/ScientificFigureLibrary (58 stars, last pushed 2d ago), licensed MIT. It adds 57 tokens to every session and 585 once invoked, about $0.0003 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 2026-09-06.
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