Full-Paper Markdown Reader — Router

SkillDocs & knowledge

Lets your agent turn academic papers into side-by-side Chinese-English Markdown readers with equations and figures preserved.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Full-Paper Markdown Reader — Router skill

About this capability

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 instea

What this skill tells your AI

The instructions your AI receives, as published by yuan1z0825/nature-skills in skills/nature-reader/SKILL.md and read by ahel’s review.

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:

  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.

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.jsonreferences/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.

Signals

GitHub stars
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Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
nature-reader
Source
github.com/yuan1z0825/nature-skills