nature-paper-to-patent

Imported from yuan1z0825/nature-skills (skills/nature-paper-to-patent/SKILL.md) via skills.sh. Install upstream with npx skills add yuan1z0825/nature-skills --skill nature-paper-to-patent. Copyright stays with the author.

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Never infer inventorship, ownership, unpublished implementation details, publication dates, prior-art conclusions, or legal sufficiency.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:

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.