nature-academic-search
Multi-source literature search, citation verification, strict independent other-citation audits, article-level citation metric tables, influential citer…
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,
$ npx -y skills add Yuan1z0825/nature-skills --skill nature-reader --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/nature-readerContext preview
The summary Claude sees to decide when to auto-load this skill.
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,
name: nature-reader description: "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." metadata: version: "2.1.1" author: Community contribution, refactored into static/dynamic layers
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.
Read [manifest.yaml](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.
Decide the `source_format` value using the manifest's `detect:` hint and the user's input:
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.
Read the file mapped for the detected `source_format`. Do **not** read every fragment in `static/`. Load only what step 2 selected.
Apply the loaded fragments in this priority order:
1. Core principles (`core/principles.md`) — bilingual reader by default, translate for meaning, never degrade to a summary, copyright caution. 2. Source-format fragment — how to extract text, figures, and tables for this input. 3. Reading workflow (`core/workflow.md`) — the six-step source-map-first process. 4. 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.
The files under `references/` are deep references, not defaults. Open them on demand per the `references.on_demand` table in the manifest:
Repo: Yuan1z0825/nature-skills
Multi-source literature search, citation verification, strict independent other-citation audits, article-level citation metric tables, influential citer…
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