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nature-paper-to-patent — Claude Code skill: patent drafts

Drafts Chinese patent documents from research papers or inventor materials, with claims tied to source evidence. Useful for disclosure analysis, claim drafting, and paper-to-patent audits.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add Yuan1z0825/nature-skills --skill nature-paper-to-patent -a claude-code
Open on GitHub

What nature-paper-to-patent does

The skill routes work by source format, task, and invention type, then builds a source map and evidence ledger. Each material claim feature must point to paper text, an equation, a figure, or supplementary evidence. Unsupported features are kept out of formal claims.

For a full application, it drafts claims first and aligns the specification, figures, embodiments, and abstract to them. Technical disclosures are produced as timestamped Markdown and matching DOCX, with Mermaid diagrams rendered through the disclosure scripts. Algorithmic inventions retain supported formulas as editable Office Math. Check the intermediate artifacts: formal claims come only after the workflow gates pass.

Formal packages use scripts/validate_patent_draft.py and scripts/build_patent_package.py; disclosures have separate checks and Mermaid/Word rendering. Python is needed to run the validation and build commands. The package is a drafting aid for inventor and patent-professional review, not a patentability or infringement opinion, or a filing guarantee.

What it helps with

  • draft claims from a research paper
  • map claim features to source evidence
  • prepare a technical disclosure as Markdown and DOCX
  • audit a patent draft against its source paper

Example prompts for the agent

  • Draft a Chinese patent application from this paper and map each material claim feature to its source.
  • Create a claim set from these inventor materials; list unsupported details as questions for confirmation.
  • Audit this patent draft against the paper and build the DOCX package.

How to install nature-paper-to-patent

1Skills CLI (Vercel)

npx skills add Yuan1z0825/nature-skills --skill nature-paper-to-patent -a claude-code

2Manually: put the files in place

~/.claude/skills/nature-paper-to-patent/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/nature-paper-to-patent/

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Questions about nature-paper-to-patent

How do I install nature-paper-to-patent in Claude Code?

Run npx skills add Yuan1z0825/nature-skills --skill nature-paper-to-patent -a claude-code, then run the same command again. The skill file is at ~/.claude/skills/nature-paper-to-patent/SKILL.md.

What does nature-paper-to-patent do?

It turns research papers or inventor materials into Chinese patent-document drafts. Formal claim features are linked to evidence in the supplied sources.

How does it validate a patent package?

Run python scripts/validate_patent_draft.py draft.json and python scripts/build_patent_package.py draft.json --output-dir outputs --prefix patent. Resolve validation errors and review warnings against the source.

Source text

SKILL.md · Apache-2.0
---
name: nature-paper-to-patent
description: "Turn research papers or inventor materials into evidence-grounded Chinese invention patent drafts and technical disclosures. Use for 技术交底书、专利撰写、现有技术对比 and Chinese DOCX patent packages; not general manuscript writing."
---

# Paper to Chinese Patent

Use this file as the router for the patent-drafting workflow. Do not draft the
application directly from the paper abstract or contribution list.

## 1. Load the workflow

Read `manifest.yaml`, then read every file under `always_load`.

Detect these axes from the user's files and request:

- `source_format`: selectable PDF, scanned PDF, pasted text, or mixed project;
- `task_mode`: full draft, claim set, disclosure analysis, technical
  disclosure, disclosure iteration, or paper-patent audit;
- `invention_type`: algorithm/software, apparatus/system, process/material, or mixed.

State the detected values in one short line. Load only the matching fragments
declared in the manifest. Load detailed references only when their condition
applies.

## 2. Preserve source grounding

Create stable source IDs before drafting:

- `P001...` for paper text blocks;
- `E001...` for equations;
- `F001...` for source figures;
- `C001...` for source-code or supplementary evidence.

Every material feature in a formal claim must map to one or more source IDs.
Use only `explicit`, `inherent`, `needs-confirmation`, or `unsupported` as
support states. Exclude `unsupported` features from formal claims.

Never infer inventorship, ownership, unpublished implementation details,
publication dates, prior-art conclusions, or legal sufficiency. Use
`[TO CONFIRM: specific question]` outside formal claims when facts are missing.

## 3. Draft through stage gates

For `full-draft`, `claim-set`, `disclosure-analysis`, and `paper-patent-audit`,
complete the stages in `static/core/workflow.md` in order. Persist the
intermediate artifacts specified there. Do not move to formal claims until the
source map, terminology ledger, inventories, evidence ledger, and invention
concept pass their gates.

For `technical-disclosure`, follow the ordered prompt references in
`static/fragments/task/technical-disclosure.md`. For `disclosure-iteration`,
follow `static/fragments/task/disclosure-iteration.md` and preserve the prior
draft instead of restarting the formal application workflow.

For a full application, draft claims first, then align the specification,
figures, embodiments, and abstract to the claim terminology and step order.

## 4. Produce Chinese formal documents

Agent-facing analysis may use the user's preferred language. Produce formal
Chinese patent deliverables in Chinese when the task is a formal application
package:

- 权利要求书;
- 说明书;
- 说明书摘要;
- 摘要附图;
- figure labels and descriptions.

For `technical-disclosure` and `disclosure-iteration`, produce the Chinese
technical disclosure (`技术交底书`) as timestamped Markdown plus matching DOCX,
with Mermaid system/process diagrams rendered through `scripts/disclosure/`.

For algorithmic inventions, retain source-supported core formulas, define every
symbol, explain each formula's technical operation, and render formulas as
native editable Office Math in DOCX. Do not use plain LaTeX strings as the
visible formula.

Generate the main flowchart from the ordered steps of the principal method
claim. Its final node must name the concrete domain output, such as a defect
detection result, target pose, state estimate, or control instruction. Reuse
the same main figure as the abstract figure and a specification figure.

## 5. Validate before delivery

For formal application packages, populate the structured draft described in
`references/draft-schema.md`, then run:

```bash
python scripts/validate_patent_draft.py draft.json
python scripts/build_patent_package.py draft.json --output-dir outputs --prefix patent
```

Resolve all validation `ERROR` findings. Review every `WARNING` against the
source. Label the result `incomplete draft` when a required quality threshold
in `static/core/output-contract.md` is not met.

For technical disclosures, run the internal checks in
`references/disclosure/disclosure_self_check.md`, render Mermaid/Word outputs
with `scripts/disclosure/mermaid_render.py`, and resolve formula, parameter,
prior-art URL, and chapter-consistency issues before delivery.

The generated package is a drafting aid for inventor and patent-professional
review, not a patentability opinion, infringement opinion, or filing guarantee.

© Yuan1z0825 · Apache-2.0 · Yuan1z0825/nature-skills

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