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 shikaijieskj/science-skills --skill science-figuregit clone --depth 1 https://github.com/shikaijieskj/science-skillsWrote 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/shikaijieskj/science-skills/science-figure)<a href="https://agentmods.dev/skills/shikaijieskj/science-skills/science-figure"><img src="https://agentmods.dev/badge/skills/shikaijieskj/science-skills/science-figure/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/shikaijieskj/science-skills/science-figure"><img src="https://agentmods.dev/badge/skills/shikaijieskj/science-skills/science-figure.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00086 | $0.00630 |
| Opus 5 | $0.00043 | $0.00315 |
| Sonnet 5 | $0.00017 | $0.00126 |
| Haiku 4.5 | $0.00009 | $0.00063 |
Grade A, and why
science-figure 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 12d 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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Science Figure
Use this skill before plotting or rewriting legends. A Science-family figure is an evidence argument, not a decorative arrangement.
First move: figure contract
Before editing or making a figure, define:
- core conclusion
- target audience
- panel list and each panel's question
- evidence hierarchy
- source data for each quantitative claim
- likely reviewer risk
- journal and article type, if known
If the user has not supplied data, create a panel plan and legend scaffold rather than fabricating plots.
Open extra files
| File | Open when |
|---|---|
| references/figure-contract.md | Need to convert results into panel map, evidence hierarchy, or reviewer-risk checks |
| references/legend-and-panel-style.md | Need legend structure, panel titles, typography, color, or abbreviation rules |
| references/qa-checklist.md | Before final delivery or when auditing an existing figure |
Figure workflow
- State the figure's one-sentence conclusion.
- Assign one job per panel:
context,design,validation,main result,mechanism,comparison,generalization, orlimitation. - Order panels by reader logic, not by experiment chronology.
- Remove redundant panels unless they test different risks.
- Map every claim in the legend to a panel, method, statistic, or source-data file.
- Audit visual encoding:
- color means the same thing across panels
- axes and units are explicit
- error bars and sample sizes are defined
- statistical tests are specified where needed
- image panels have scale bars and acquisition context
- Return the figure plan, legend, and unresolved data/source issues.
Science-family design defaults
- Favor dense but legible multi-panel evidence.
- Put the strongest result in the visual position the reader sees early.
- Use muted neutral structure plus a small number of meaningful accent colors.
- Avoid rainbow palettes unless the data are continuous and colorbar-labeled.
- Never use color alone to encode categorical distinctions.
- Legends should explain what was done and what is shown, not claim more than the data support.
What ships with it
4 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.
- 12d ago First seen · 75 lines · 86 tokens per session scan A 20c3c6cbc5cf
science-figure is a skill published in the GitHub repository shikaijieskj/science-skills (5 stars, last pushed 3mo ago), licensed MIT. It adds 86 tokens to every session and 630 once invoked, about $0.0004 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 2026-08-31.
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