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 yniantongtian-oss/nature-skills --skill nature-figuregit clone --depth 1 https://github.com/yniantongtian-oss/nature-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/yniantongtian-oss/nature-skills/nature-figure)<a href="https://agentmods.dev/skills/yniantongtian-oss/nature-skills/nature-figure"><img src="https://agentmods.dev/badge/skills/yniantongtian-oss/nature-skills/nature-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/yniantongtian-oss/nature-skills/nature-figure"><img src="https://agentmods.dev/badge/skills/yniantongtian-oss/nature-skills/nature-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 | $0.00149 | $0.01057 |
| Opus 5 | $0.00075 | $0.00528 |
| Sonnet 5 | $0.00030 | $0.00211 |
| Haiku 4.5 | $0.00015 | $0.00106 |
Grade A, and why
nature-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 — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Nature Figure Making — Router
This skill is split into two layers:
- A static layer under
static/that holds versioned, reusable content fragments (the figure contract and default stance, plus a per-backend quick-start for Python and R). - A dynamic layer (this file plus
manifest.yaml) that detects the plotting backend and loads only the fragment needed for the current job. The large design, API, pattern, and QA material lives in on-demand references.
Do not try to apply the figure logic from memory or from this router. Always load fragments from disk as described below.
Routing protocol
Follow these five steps every time the skill is invoked.
1. Load the manifest and the core layer
Read manifest.yaml. It declares the backend axis, the allowed values, and the file paths each value maps to.
Also read every file listed under always_load (static/core/contract.md and static/core/stance.md). These hold the figure contract, the backend gate, the missing-runtime rule, the privacy rule, and the default operating stance that apply to every figure job.
2. Resolve the backend — a blocking gate
Backend selection blocks everything else. Decide the backend value only from an explicit user choice or a clearly language-specific input file/workflow:
python— matplotlib / seaborn.r— ggplot2 / patchwork / ComplexHeatmap.
If the user has not explicitly chosen, ask exactly one concise question — Python or R? — and stop. Do not default, guess, generate mock data, or write scripts before the answer. Only recommend a backend when the user explicitly asks you to choose; then use references/backend-selection.md, state the reason, and proceed. Once selected, the backend is exclusive for all drawing, previewing, exporting, and visual QA (see core/contract.md).
3. Load the matching backend fragment
After the backend is resolved, Read the mapped fragment (static/fragments/backend/python.md or static/fragments/backend/r.md). It carries the backend-only execution rule and the publication quick-start (rcParams/theme and export helper). Do not load the other backend's fragment.
What ships with it
60 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.
- .gitignore 10 B
- assets/chart-atlas/atlas-01-bar-charts.png 122 KB
- assets/chart-atlas/atlas-02-line-trends.png 414 KB
- assets/chart-atlas/atlas-03-heatmaps.png 156 KB
- assets/chart-atlas/atlas-04-scatter-bubble.png 474 KB
- assets/chart-atlas/atlas-05-radar-polar.png 615 KB
- assets/chart-atlas/atlas-06-distributions.png 228 KB
- assets/chart-atlas/atlas-07-forest-interval.png 264 KB
- assets/chart-atlas/atlas-08-area-stacked.png 327 KB
- assets/chart-atlas/atlas-09-image-plates.png 351 KB
- assets/chart-atlas/atlas-10-network-matrix.png 305 KB
- assets/figures4papers/assets/Dispersion_motivation.png 818 KB
- assets/figures4papers/assets/Dispersion_observation_distillation.png 602 KB
- assets/figures4papers/assets/Dispersion_observation.png 790 KB
- assets/figures4papers/assets/ImmunoStruct_contrastive.png 490 KB
- assets/figures4papers/assets/ImmunoStruct_results_CEDAR.png 1252 KB
- assets/figures4papers/assets/ImmunoStruct_results_IEDB.png 934 KB
- assets/figures4papers/assets/ImmunoStruct_schematic.png 950 KB
- assets/figures4papers/assets/RNAGenScape_schematic.png 977 KB
- assets/figures4papers/figure_brainteaser/figures/brute_force.png 1712 KB
- assets/figures4papers/figure_brainteaser/figures/correctness_by_category.png 640 KB
- assets/figures4papers/figure_brainteaser/figures/correctness_by_subcategory.png 1075 KB
- assets/figures4papers/figure_brainteaser/figures/rewriting.png 400 KB
- assets/figures4papers/figure_brainteaser/figures/selfcorrection_math.png 597 KB
- assets/figures4papers/figure_brainteaser/plot_brute_force.py 9.9 KB runs code
- assets/figures4papers/figure_brainteaser/plot_correctness_by_category.py 6.3 KB runs code
- assets/figures4papers/figure_brainteaser/plot_correctness_by_subcategory.py 6.4 KB runs code
- assets/figures4papers/figure_brainteaser/plot_rewriting.py 3.6 KB runs code
- assets/figures4papers/figure_brainteaser/plot_selfcorrection_math.py 3.9 KB runs code
- assets/figures4papers/figure_CellSpliceNet/figures/ablation.png 347 KB
- assets/figures4papers/figure_CellSpliceNet/figures/comparison.png 794 KB
- assets/figures4papers/figure_CellSpliceNet/plot_ablation.py 2.9 KB runs code
- assets/figures4papers/figure_CellSpliceNet/plot_comparison.py 3.8 KB runs code
- assets/figures4papers/figure_Cflows/diffusion_swiss_roll.py 3.5 KB runs code
- assets/figures4papers/figure_Cflows/figures/diffusion_swiss_roll.png 1753 KB
- assets/figures4papers/figure_Cflows/figures/fig2_comparison_GeneRegulatory.pdf 24 KB
- assets/figures4papers/figure_Cflows/figures/fig2_comparison_GeneRegulatory.png 281 KB
- assets/figures4papers/figure_Cflows/figures/fig2_comparison_Trajectory.pdf 19 KB
- assets/figures4papers/figure_Cflows/figures/fig2_comparison_Trajectory.png 379 KB
- assets/figures4papers/figure_Cflows/figures/figX_comparison_Ablation.pdf 19 KB
- assets/figures4papers/figure_Cflows/figures/figX_comparison_Ablation.png 321 KB
- assets/figures4papers/figure_Cflows/plot_comparison_Ablation.py 2.4 KB runs code
- assets/figures4papers/figure_Cflows/plot_comparison_GeneRegulatory.py 3.0 KB runs code
- assets/figures4papers/figure_Cflows/plot_comparison_Trajectory.py 2.9 KB runs code
- assets/figures4papers/figure_Dispersion/figures/idea.png 376 KB
- assets/figures4papers/figure_Dispersion/figures/illustration.png 745 KB
- assets/figures4papers/figure_Dispersion/plot_idea.py 2.4 KB runs code
- assets/figures4papers/figure_Dispersion/plot_illustration.py 15 KB runs code
- assets/figures4papers/figure_FPGM/figures/freq_prior.png 626 KB
- assets/figures4papers/figure_FPGM/plot_freq_prior.py 6.4 KB runs code
- assets/figures4papers/figure_ImmunoStruct/figures/bars_ablation_Cancer.png 798 KB
- assets/figures4papers/figure_ImmunoStruct/figures/bars_ablation_IEDB.png 1133 KB
- assets/figures4papers/figure_ImmunoStruct/figures/bars_comparison_Cancer.png 781 KB
- assets/figures4papers/figure_ImmunoStruct/figures/bars_comparison_IEDB.png 740 KB
- assets/figures4papers/figure_ImmunoStruct/plot_bars.py 7.5 KB runs code
- assets/figures4papers/figure_ImmunoStruct/raw_data.py 4.4 KB runs code
- assets/figures4papers/figure_ophthal_review/figures/composition_heatmap.png 273 KB
- assets/figures4papers/figure_ophthal_review/figures/trend_by_month.png 356 KB
- assets/figures4papers/figure_ophthal_review/plot_composition.py 3.0 KB runs code
- assets/figures4papers/figure_ophthal_review/plot_trend.py 5.4 KB runs code
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 · 61 lines · 149 tokens per session scan A 8699cee0c047
nature-figure is a skill published in the GitHub repository yniantongtian-oss/nature-skills (24 stars, last pushed 3mo ago), licensed MIT. It adds 149 tokens to every session and 1,057 once invoked, about $0.0007 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 2026-08-30.
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