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-readergit 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-reader)<a href="https://agentmods.dev/skills/yuan1z0825/nature-skills/nature-reader"><img src="https://agentmods.dev/badge/skills/yuan1z0825/nature-skills/nature-reader/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-reader"><img src="https://agentmods.dev/badge/skills/yuan1z0825/nature-skills/nature-reader.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- 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 | $0.00056 | $0.00832 |
| Opus 5.5 | $0.00022 | $0.00333 |
| Sonnet 5.5 | $0.00011 | $0.00166 |
| Haiku 4.5 | $0.00006 | $0.00083 |
Grade A, and why
nature-reader 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 1mo 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- nature-reader — 92% identical, 33 lines differ
- nature-reader — 92% identical, 31 lines differ
How it starts
The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Full-Paper Markdown Reader — Router
Routing protocol
First distinguish creating a reader from answering a question or translating an excerpt.
For a source-linked question, read references/grounding-rules.md and inspect only the relevant
source material; reuse existing source-map IDs when available. Do not regenerate the reader or
require a full source map before answering. For an explicit excerpt request, apply extraction,
translation, and grounding rules to that excerpt. The full-artifact workflow below applies when
the user requests a reader or full-paper translation.
For a new task, load the core and matching resources below. Reuse already loaded guidance on follow-ups; load more only when the task needs it.
1. Load the manifest and the core layer
Read manifest.yaml. It declares the source_format axis, the allowed values, and the file paths each value maps to.
Also read every file listed under always_load. These hold the core principles, the reading workflow, and the output contract that apply to every reading job, plus the shared Terminology Ledger used to build the recurring-term table.
2. Detect the source format
Decide the source_format value using the manifest's detect: hint and the user's input:
pdf-text— selectable-text PDF. Default.scanned-pdf— image-only or OCR-required PDF.html— publisher or preprint HTML page.doi-arxiv— a bare DOI or arXiv link that must be resolved first.pasted-text— pasted prose or notes with no retrievable original layout.
State the detected value in one short line to the user before processing, so they can correct you cheaply. A source may map to more than one value (for example a DOI that resolves to a PDF); load the resolution fragment first, then the fragment for the resolved artifact.
3. Load the matching fragment(s)
Read the file mapped for the detected source_format. Do not read every fragment in static/. Load only what step 2 selected.
What ships with it
19 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 218 B
- evals/evals.json 3.5 KB
- manifest.yaml 2.1 KB
- README_EN.md 2.3 KB
- README.md 2.1 KB
- references/article-anatomy.md 3.3 KB
- references/equation-handling.md 5.1 KB
- references/figure-extraction.md 2.0 KB
- references/grounding-rules.md 2.2 KB
- references/output-spec.md 4.9 KB
- scripts/validate_reader_math.py 17 KB runs code
- static/core/output-contract.md 2.1 KB
- static/core/principles.md 3.7 KB
- static/core/workflow.md 5.1 KB
- static/fragments/source/doi-arxiv.md 1.2 KB
- static/fragments/source/html.md 1.2 KB
- static/fragments/source/pasted-text.md 1.2 KB
- static/fragments/source/pdf-text.md 1.3 KB
- static/fragments/source/scanned-pdf.md 1.2 KB
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.
- 1mo ago Changed · -7 lines · -150 tokens per session 999a5c1b1165
- 1mo ago First seen · 72 lines · 206 tokens per session scan A fb93710f3484
nature-reader is a skill published in the GitHub repository Yuan1z0825/nature-skills (50,803 stars, last pushed 2d ago), licensed Apache-2.0. It adds 56 tokens to every session and 832 once invoked, about $0.0002 per session on Opus 5.5. 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
download-fulltext-pdf
A skill for downloading a research paper's complete PDF using an identifier such as a DOI, title, or BibTeX entry.
document-parser
Parse and extract structured content from PDFs, Word documents, and other file formats. Converts documents into clean, machine-readable text for analysis, summarization, data extraction, and content processing workflows.
report-helper
A Chinese-language research workflow that searches the internet and produces a formatted PDF report about a specified topic.
api2pdf-automation
Automate Api2pdf tasks via Rube MCP (Composio). Always search tools first for current schemas.
markdown-to-pdf
Convert Markdown (.md) files to a polished PDF with ALL images preserved and scaled to the page. Use whenever the user asks to "save this markdown as a PDF", "convert README.md to pdf", "export the .md as a pdf", "turn these notes/docs into a PDF", or wants a PDF deliverable of any GitHub-flavored Markdown document…
pdf-analyze
Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs to fill in a PDF form or programmatically process, generate, or analyze PDF documents at scale.