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Full-Paper Markdown Reader

Free

Effortlessly read and translate academic papers side-by-side.

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Free · Opens the source repo

What Full-Paper Markdown Reader does

The Full-Paper Markdown Reader skill is designed for researchers and academics who need to read, translate, and understand scholarly papers in both Chinese and English. It creates a side-by-side Markdown reader that is aware of figures, tables, and equations, ensuring that the layout of the original paper is preserved. This skill supports various input formats, including PDFs, HTML pages, and pasted text, making it versatile for different sources of academic content.

When invoked, the skill intelligently detects the source format of the input, whether it's a selectable-text PDF, a scanned PDF, or an HTML document. It then loads the appropriate fragments to process the request while adhering to core principles such as providing a bilingual reader and avoiding summary-only outputs unless explicitly requested. This ensures that users receive a comprehensive reading experience, complete with accurate translations and proper placement of figures and tables.

The skill also emphasizes the importance of maintaining source integrity by keeping exact anchors for every block of text. This feature is particularly useful for users who need to reference specific sections or data within a paper. Additionally, the skill's architecture allows for easy updates and the addition of new source formats, making it a reliable tool for ongoing academic work.

Overall, the Full-Paper Markdown Reader is an essential tool for anyone engaged in academic research or translation, providing a streamlined way to access and comprehend complex scholarly materials in a bilingual format.

When to use it

Use this skill when you need to read or translate academic papers, particularly when working with complex formats that include figures and equations.

When not to use it

This skill may not be suitable for casual reading or non-academic texts, as it is specifically tailored for scholarly articles and requires a structured input format.

What you can build with it

Translating a Research Paper

Use the skill to translate a complex research paper from English to Chinese while preserving the layout and figures.

Reading a Conference Submission

Invoke the skill to read and understand a conference submission in PDF format, ensuring all elements are accurately represented.

Extracting Data from an Article

Utilize the skill to extract specific tables and figures from an academic article, placing them in the correct context within the translation.

How to install Full-Paper Markdown Reader

View source

1. Install with the skills CLI

npx skills add yuan1z0825/nature-skills/nature-reader --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by yuan1z0825

Full-Paper Markdown Reader — Router

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:

  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.

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-writing and nature-polishing so shared content lives in nature-shared/.

Frequently asked questions about Full-Paper Markdown Reader

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