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 poplarity/dsh-science-workbench --skill figure-stylegit clone --depth 1 https://github.com/poplarity/dsh-science-workbenchWrote 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/poplarity/dsh-science-workbench/figure-style)<a href="https://agentmods.dev/skills/poplarity/dsh-science-workbench/figure-style"><img src="https://agentmods.dev/badge/skills/poplarity/dsh-science-workbench/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/poplarity/dsh-science-workbench/figure-style"><img src="https://agentmods.dev/badge/skills/poplarity/dsh-science-workbench/figure-style.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 | $0.00167 | $0.04234 |
| Opus 5 | $0.00084 | $0.02117 |
| Sonnet 5 | $0.00033 | $0.00847 |
| Haiku 4.5 | $0.00017 | $0.00423 |
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 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.
This is a copy
86% identical to figure-style — 159 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 344 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bundled with dsh-science-workbench — adapted from Anthropic Claude Science's built-in skills (extracted via the AcademicForge project), Apache-2.0.
Integration in this workbench: apply these rules when writing
bio_run_cellcode. The helperkernel.py(withapply_figure_style,panel_letter,panel_crops, …) ships beside this SKILL.md — copy it into the project'scode/once if you want to call the helpers from cells:cp <this-skill-dir>/kernel.py <project>/code/figure-style-kernel.py, then in the cellexec(open("code/figure-style-kernel.py").read()). Or apply the rules inline without the kernel.
Publication-Grade Figure Rules
A checklist for correct, legible, internally-consistent scientific figures. This
skill does not impose a visual house style — frame, font, and palette are
parameters. Load it and call apply_figure_style() before any plot.
§0 Scope
§1–§3, §8, and §9 are correctness — they apply to every plot, in every
context, and have no aesthetic content. §4–§7 are guidance — defaults that
produce a clean result but that a deliberate alternative can override
(individual rules inside §4–§7 that state a factual/perceptual invariant — e.g.
§4.4 semantic-zero centring, §4.5 CVD, §6.9 leader anchoring — still bind). On
its own, this skill is the inner tier (make one plot good); figure-composer
and paper-narrative supply multi-panel and whole-paper context.
§1 Data fidelity & self-consistency
1.1 Excluded rows. A row marked excluded or flagged in the source data is either omitted entirely or drawn with a visually distinct open/hatched marker and named in the key. It never enters a summary statistic plotted alongside the included rows.
1.2 Comparable conditions only. Arms measured under non-comparable conditions (different N, epoch budget, initialisation, protocol) are not plotted as visual peers. Separate them with a facet break or a marker on the label, and state the difference once in the caption.
What ships with it
2 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 · 344 lines · 167 tokens per session scan A f606bd6442c4
figure-style is a skill published in the GitHub repository poplarity/dsh-science-workbench (8 stars, last pushed 17d ago), licensed MIT. It adds 167 tokens to every session and 4,234 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to figure-style, differing in 159 lines, and is treated as a copy.
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