nature-reader
Skill0 starsChanged 2 months agoMITView on GitHub
Build full-paper Chinese-English side-by-side, figure/table/equation-aware, source-grounded Markdown readers for journal or conference papers from PDF, DOI, arXiv, publisher HTML, or pasted text. Use whenever the user asks to translate or read a paper, make 中英文对照/原文对照/全文翻译解读, render equations instead of exposing raw LaTeX, extract figures or tables into the right positions, preserve figure/table placement near relevant prose, or keep exact source anchors for every block. This skill must not degrade into a summary-only output unless the user explicitly asks for a summary. Also trigger on general paper-reading and translation requests even without the word "Nature", such as reading/translating an academic paper, literature reading, understanding a paper, and Chinese phrasings like 读论文、精读论文、论文翻译、文献翻译、文献阅读、学术阅读、帮我读这篇文章、翻译这篇paper.
8 other projects use a version of this, 5 of them edited.
Adopted by
Most recently taken up by
- dragonadam/nature-skillsedited, first seen Oct 25, 2026
- Luooops/skillsedited, first seen Oct 13, 2026
- yanjumlinnb-boop/nature-skillsedited, first seen Oct 8, 2026
- Yang1Bai/nature-paper-hubtheir own version, first seen Sep 28, 2026
- Yuan1z0825/nature-skillsedited, first seen Aug 31, 2026
- zh123012/claude-skillsedited, first seen Jul 29, 2026
Other versions8 projects use a version of this.
Word for word · 0
None found.
Edited · 5
- Yuan1z0825/nature-skills★ 53k74% same
- yanjumlinnb-boop/nature-skills★ 1496% same
- dragonadam/nature-skills★ 496% same
- Luooops/skills★ 174% same
- zh123012/claude-skills★ 197% same
Wrote their own version · 3
- Yang1Bai/nature-paper-hub★ 18same name
- Delagong950/nature-skills★ 4same name
- vcis-wangchenxu/agent_nature-skills★ 4same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository21 other files it gives its agents.
- journal-style-learnSkill
- nature-academic-searchSkill
- nature-citationSkill
- nature-dataSkill
- nature-downloaderSkill
- nature-experiment-logSkill
- nature-figure-prompt-onlySkill
- nature-figureSkill
- nature-image2pptSkill
- nature-literature-pipelineSkill
- nature-paper2pptSkill
- nature-paper-cardSkill
- nature-paper-to-patentSkill
- nature-polishingSkill
- researchwriteSkill
- nature-ref-verifierSkill
- nature-responseSkill
- nature-reviewerSkill
- nature-sharedSkill
- nature-statisticsSkill
- nature-writingSkill
The file
We split this skill into the rules it gives an agent
8 rules. 0 are common, 4 are distinctive, and 4 are very specific to this project.
0
Common
Most of the 8 edited versions we read keep these.
4
Distinctive
This author's own choices. Worth a look.
4
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 17
Treat a source journal as metadata: preserve the source’s facts and structure.
- Distinctive: line 19
Keep this skill’s original source-processing workflow.
- Very specific: line 27
Only if journal fit or submission requirements are requested, read ../nature-shared/journal-formats/eswa.md.
- Distinctive: line 37
Do not try to apply the reading logic from memory or from this router.
- Distinctive: line 41
Follow these five steps every time the skill is invoked.
- Very specific: line 45
Read manifest.yaml. It declares the source_format axis, the allowed values, and the file paths each value maps to.
- Very specific: line 63
Read the file mapped for the detected source_format.
- Very specific: line 76
If constraints prevent full processing, still create a draft reader and label missing pages, figures, or low-confidence crops in …
“Common” is measured: kept by at least 6 in 10 of the 8 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Full-Paper Markdown Reader — Router
Additional configured journals
For Applied Soft Computing (ASC), Engineering Applications of Artificial
Intelligence (EAAI), ISA Transactions, Knowledge-Based Systems (KBS),
Measurement, Neurocomputing, or IEEE Transactions on Reliability, use
../nature-shared/journal-formats/index.md to resolve the exact journal.
Treat a source journal as metadata: preserve the source’s facts and structure.
Load submission constraints only when target formatting or fit is requested.
Keep this skill’s original source-processing workflow.
ESWA journal context
Recognize Expert Systems with Applications (ESWA, Expert Syst. Appl.)
as the same journal, case-insensitively; distinguish similarly named titles.
Preserve the paper's original text, headings, citations and figure order.
A source-journal label does not authorize rewriting or shortening a translation.
Only if journal fit or submission requirements are requested, read
../nature-shared/journal-formats/eswa.md; otherwise keep this workflow
source-oriented without loading submission rules.
This skill is split into two layers:
- A static layer under
static/that holds versioned, reusable content fragments (core principles, the reading workflow, the output contract, and per-source-format extraction guidance). - A dynamic layer (this file plus
manifest.yaml) that detects the request's source format and loads only the fragments needed for the current job.
Do not try to apply the reading 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 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.
4. Build the reader using the loaded material
Apply the loaded fragments in this priority order:
- Core principles (
core/principles.md) — bilingual reader by default, translate for meaning, never degrade to a summary, copyright caution. - Source-format fragment — how to extract text, figures, and tables for this input.
- Reading workflow (
core/workflow.md) — the six-step source-map-first process. - Output contract (
core/output-contract.md) — required files and the pre-response verification checklist.
Build the Terminology Ledger as you translate (../nature-shared/core/terminology-ledger.md); it becomes the paper.md recurring-term table and the source_map.json glossary.
If constraints prevent full processing, still create a draft reader and label missing pages, figures, or low-confidence crops in translation_notes.md. Do not switch to summary mode.
5. Reach for references only when needed
The files under references/ are deep references, not defaults. Open them on demand per the references.on_demand table in the manifest:
- detailed figure/table cropping and placement →
references/figure-extraction.md. - exact field schema for
paper.md/source_map.json→references/output-spec.md. - equations, mathematical expressions, chemical formulae, or image-only formulae →
references/equation-handling.md. - answering follow-up questions with source citations →
references/grounding-rules.md.
Why this split
- The static layer is versioned and reviewable. Adding a new source format is one new fragment plus one manifest line.
- The dynamic layer keeps each invocation cheap: only the fragment relevant to this input enters context.
- The router itself is short on purpose. Update fragments, not this file, when adding scope.
- This structure mirrors
nature-writingandnature-polishingso shared content lives innature-shared/.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

