nature-paper-to-patent
yuan1z0825/nature-skills
Transform research papers into evidence-grounded Chinese invention patent drafts and technical disclosures.
What is nature-paper-to-patent?
Converts research papers or inventor materials into Chinese patent applications, technical disclosures (技术交底书), and formal patent packages. Use this for structured patent drafting with source grounding, claim validation, and DOCX delivery—not for general manuscript writing.
- Maps source materials (papers, equations, figures, code) to stable evidence IDs before drafting
- Detects invention type (algorithm, apparatus, process, material) and task mode (full draft, claims, disclosure, audit)
- Produces formal Chinese patent documents: 权利要求书, 说明书, 摘要, and abstract figures
- Validates claims against source evidence using explicit/inherent/needs-confirmation/unsupported states
- Generates Mermaid flowcharts and Office Math formulas for algorithmic inventions
- Outputs timestamped technical disclosures as Markdown plus editable DOCX
How to install nature-paper-to-patent
npx skills add https://github.com/yuan1z0825/nature-skills --skill nature-paper-to-patent- Python 3.7+ for validation and build scripts
- Access to source materials: research paper (PDF or text), equations, figures, and supplementary code or evidence
- Familiarity with Chinese patent terminology (权利要求书, 说明书, 技术交底书)
How to use nature-paper-to-patent
- 1.Load the workflow by reading manifest.yaml and always_load files
- 2.Provide source materials and specify: source_format (PDF/text/mixed), task_mode (full draft/claims/disclosure/audit), and invention_type (algorithm/apparatus/process/material)
- 3.Create source IDs (P001 for paper blocks, E001 for equations, F001 for figures, C001 for code) and map all features to evidence
- 4.Complete stage gates in order: source map → terminology ledger → inventories → evidence ledger → invention concept
- 5.Draft claims first, then align specification, figures, embodiments, and abstract to claim terminology
- 6.Run validation scripts (validate_patent_draft.py, build_patent_package.py) and resolve all ERROR findings before delivery
Use cases
- Convert a published research paper into a complete Chinese patent application package with validated claims
- Draft a technical disclosure (技术交底书) from inventor notes with system diagrams and formula definitions
- Audit an existing paper-to-patent workflow to identify unsupported claims or missing source grounding
- Iterate on a technical disclosure by preserving prior drafts and refining specific sections
- Generate claim sets for apparatus or process inventions with evidence-mapped feature lists
- Patent professionals and inventors preparing Chinese patent applications
- Researchers converting academic papers into patentable inventions
- Technical teams documenting algorithmic or system innovations for IP protection
- Organizations conducting patent audits or disclosure reviews
nature-paper-to-patent FAQ
A full draft produces a complete formal Chinese patent application package (权利要求书, 说明书, 摘要). A technical disclosure (技术交底书) is a timestamped internal document in Markdown and DOCX format, typically used for inventor review and prior-art documentation before formal filing.
Every material feature in a claim must map to one or more source IDs (P001, E001, F001, C001). Features are classified as explicit (directly stated), inherent (logically follows), needs-confirmation (requires clarification), or unsupported (excluded from formal claims). This ensures claims are evidence-backed and defensible.
This skill is designed specifically for Chinese patent applications and technical disclosures. Formal deliverables are produced in Chinese. For other jurisdictions, consult a patent professional or use jurisdiction-specific tools.
Unsupported features are excluded from formal claims and flagged with [TO CONFIRM: specific question]. You must either find source evidence, confirm the feature with inventors, or remove it before validation passes.
No. This is a drafting aid for inventor and patent-professional review only. It does not assess patentability, infringement risk, or filing guarantees. Always have a qualified patent attorney review the output.
Full instructions (SKILL.md)
Source of truth, from yuan1z0825/nature-skills.
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:
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.
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