nature-academic-search
Multi-source literature search, citation verification, strict independent other-citation audits, article-level citation metric tables, influential citer…
Convert scientific papers, theses, technical reports, source code, figures, inventor notes, or research manuscripts into evidence-grounded Chinese invention patent drafts and attorney-facing technical disclosure materials. Use when an AI agent must mine patent points, draft or
$ npx -y skills add Yuan1z0825/nature-skills --skill nature-paper-to-patent --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/nature-paper-to-patentContext preview
The summary Claude sees to decide when to auto-load this skill.
Convert scientific papers, theses, technical reports, source code, figures, inventor notes, or research manuscripts into evidence-grounded Chinese invention patent drafts and attorney-facing technical disclosure materials. Use when an AI agent must mine patent points, draft or
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."
Use this file as the router for the patent-drafting workflow. Do not draft the application directly from the paper abstract or contribution list.
Read `manifest.yaml`, then read every file under `always_load`.
Detect these axes from the user's files and request:
disclosure, disclosure iteration, or paper-patent audit;
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.
Create stable source IDs before drafting:
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Never infer inventorship, ownership, unpublished implementation details, publication dates, prior-art conclusions, or legal sufficiency.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.
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.
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:
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.
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.
Repo: Yuan1z0825/nature-skills
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