
nature-reader
Create source-grounded Chinese-English paper readers with aligned text, figures, tables, and equations. Use for 全文翻译、中英文对照、论文精读 or source-linked questions about a paper; respect a requested excerpt or question without generating a full reader.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/yuan1z0825/nature-skills --skill nature-reader- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads nature-reader automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
Security audits
Independent scans of the skill's instructions and bundled files.
SKILL.md
The instructions your agent reads when the skill is triggered.
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.
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.
FAQ
What does the nature-reader skill do?
Create source-grounded Chinese-English paper readers with aligned text, figures, tables, and equations. Use for 全文翻译、中英文对照、论文精读 or source-linked questions about a paper; respect a requested excerpt or question without generating a full reader.
How do I install nature-reader?
Run npx skills add https://github.com/yuan1z0825/nature-skills --skill nature-reader in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/nature-reader/ (personal) or .claude/skills/nature-reader/ (project).
Which AI agents can use nature-reader?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is nature-reader safe to install?
Security partners have reviewed it: Gen Agent Trust Hub passed; Socket passed; Snyk flagged items to review. As with any skill, read the SKILL.md and bundled scripts before installing.
Who maintains nature-reader?
It is published by yuan1z0825 in yuan1z0825/nature-skills. It has 15,054 recorded installs.
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