Nature Skills is a collection of reusable skills that help AI agents handle academic writing and scientific visualization. Researchers and AI-assisted scholars use it to turn research tasks into repeatable workflows and usable outputs. The catalogue entries are skills from this collection.
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 Yuan1z0825/nature-skills --skill nature-sharedgit clone --depth 1 https://github.com/Yuan1z0825/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/yuan1z0825/nature-skills/nature-shared)<a href="https://agentmods.dev/skills/yuan1z0825/nature-skills/nature-shared"><img src="https://agentmods.dev/badge/skills/yuan1z0825/nature-skills/nature-shared/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/yuan1z0825/nature-skills/nature-shared"><img src="https://agentmods.dev/badge/skills/yuan1z0825/nature-skills/nature-shared.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00059 | $0.00435 |
| Opus 5 | $0.00030 | $0.00217 |
| Sonnet 5 | $0.00012 | $0.00087 |
| Haiku 4.5 | $0.00006 | $0.00044 |
Grade A, and why
nature-shared 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 13d 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.
What it actually says
Nature Shared References
Use this package only as a dependency of another installed Nature skill.
- Load the exact referenced file; do not preload the whole package.
- Treat
core/andjournal-formats/as shared definitions, not standalone workflows. - Use
journal-formats/nature.mdonly for the flagship journal Nature andcore/research-compliance.mdonly when its specialist applicability gate is triggered. - Use
journal-formats/nature-machine-intelligence.mdfor exact NMI article types, limits, initial-submission files, data/code duties and production requirements; do not import flagship Nature or Nature Communications limits. - Use
core/main-text-discipline.mdfor result placement, main-text compression, revision accretion, caption/SI allocation, and claim-repetition checks. - Use
core/nature-results-discussion.mdfor corpus-derived Nature-style Results claim escalation, evidence-bound local interpretation, and Discussion synthesis; do not present it as official journal policy. - Use
core/discussion-argument-language.mdfor journal-general Discussion function sequencing, reverse-funnel control, evidence-calibrated modality, claim-specific limitations, and uncertainty-driven future work. - Use
core/nature-introduction.mdfor corpus-derived Nature-style problem funnels, exact knowledge gaps, literature tension, question-first novelty, and Introduction–Results alignment; do not present it as official journal policy. - Use
core/nature-abstract.mdfor corpus-derived Nature-style discovery-centred abstract compression, claim hierarchy, selective numeric support, and field-level payoff; do not present it as official journal policy. - Return to the requesting skill for task logic, output format, and final QA.
What ships with it
20 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.
- agents/openai.yaml 271 B
- core/consistency-sweep.md 7.6 KB
- core/discussion-argument-language.md 9.2 KB
- core/ethics.md 3.3 KB
- core/main-text-discipline.md 9.0 KB
- core/nature-abstract.md 7.8 KB
- core/nature-introduction.md 7.5 KB
- core/nature-results-discussion.md 10 KB
- core/paper-type-taxonomy.md 2.4 KB
- core/reader-workflow.md 977 B
- core/research-compliance.md 7.5 KB
- core/terminology-ledger.md 2.7 KB
- journal-formats/nat-comms.md 6.9 KB
- journal-formats/nature-machine-intelligence.md 19 KB
- journal-formats/nature.md 13 KB
- manifest.yaml 4.4 KB
- README_EN.md 3.4 KB
- README.md 3.3 KB
- scripts/check_consistency.py 8.7 KB runs code
- tests/test_check_consistency.py 2.2 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.
- 13d ago First seen · 34 lines · 59 tokens per session scan A 3d914e73f023
nature-shared is a skill published in the GitHub repository Yuan1z0825/nature-skills (40,913 stars, last pushed 2d ago), licensed Apache-2.0. It adds 59 tokens to every session and 435 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 2026-08-30.
Other skills, from other repositories
literature-searcher
Search CrossRef, OpenAlex, PubMed, Semantic Scholar, and optional Scopus; deduplicate results, download open-access PDFs by DOI, classify papers, monitor new results, and analyze coverage. Use when asked to search literature, monitor a topic, download an open-access paper, classify papers, or analyze literature gaps.
academic-research
Search academic papers, scholarly articles, and research publications through SandBase. Use when asked for literature review, academic citations, scholarly research, paper discovery, or scientific evidence gathering.
academic-trend-research
Research emerging academic trends by combining scholarly databases, web sources, and news to identify rising research areas, breakthrough papers, and shifting scientific consensus. Ideal for R&D teams tracking frontier science.
using-cesiumjs-skills
Use when starting any conversation involving CesiumJS development - provides orientation on available domain skills and how they activate.
latex-empirical-tables
Set up, format, fix, and clean up LaTeX regression and estimation tables in empirical economics or finance papers. Use when (a) creating a .tex, results.tex, main.tex, or preamble to display regression or estimation output from Python (pyfixest), Stata, or R — including any mention of estout, esttab, estauto, estwide…
cite-placement
Place pre-screened literature citations into a LaTeX or Word manuscript, or restyle the citations already in one. Three modes: (1) inline placement — inline \cite{}/\citet{}/\citep{} with a compiled references.bib, for author-date journals (APA, MLA, Harvard, Chicago author-date, IEEE, Vancouver); (2) footnote…