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nature-paper-to-patent

根据研究论文或发明人资料起草中文发明专利文件或技术交底书,将权利要求中的技术特征对应到原始证据,并检查术语、图示和说明书的一致性,生成供发明人及专利专业人士审阅的文档。

原文查看原文说明

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.

实测评分 未实测

查看安装方法

适用场景

  • 根据论文起草中文专利文件
  • 撰写或修改技术交底书
  • 追溯权利要求的证据来源
  • 检查权利要求、附图和说明书

中文介绍

功能

根据研究论文或发明人提供的资料,起草中文发明专利文件或技术交底书。它会为原文段落、公式、图和代码分配编号,并将权利要求中的每项技术特征对应到支持它的证据。正式申请文件按照权利要求、说明书、附图、实施例和摘要的结构展开,同时检查术语和步骤是否一致。技术交底书以 Markdown 和 DOCX 形式输出。对于算法类发明,DOCX 中的公式会采用可编辑的 Office Math 格式。

适用场景

适合将论文成果整理成中文专利草案,或准备供发明人和专利专业人士讨论的资料。也可用于修改已有技术交底书,或核对论文与专利草案的对应关系。

使用示例

  • “请根据这篇论文起草中文专利文件,并为每项权利要求标明证据来源。”
  • “请修改这份技术交底书,并生成 DOCX 文件。”
  • “请检查权利要求与原始资料的对应关系,以及附图是否与说明书一致。”

注意事项

正式交付文件使用中文。文档生成和验证会使用 Python 脚本,图示使用 Mermaid。原始资料无法支持的特征不会写入正式权利要求,未知事项会明确标出。成果是供发明人和专利专业人士审阅的草案,不提供专利性或侵权判断,也不保证申请成功。

本介绍由 AI(OpenAI Codex)根据公开的 SKILL.md 撰写。准确的规格请查看下方原文。

文档检查

AI 根据 SKILL.md 的内容检查了需要注意的操作和使用前提。评分只依据实际运行的结果(实测对比)。

安全性发送数据、删除文件、执行命令等是否有说明
B部分不足资料要求运行Python验证和生成脚本,但未说明执行前的确认步骤。
安装难易度所需工具和 API 密钥是否少且有说明
B部分不足需要使用Python和Mermaid,但未提供安装步骤和环境细节。

不计入评分。 由 AI(OpenAI Codex)于 2026年10月24日 评估。仅供参考,安装前请同时查看原文。

如果您认为评估有误,请申请复核

请写明哪一项有误以及原因。无需登录。我们会对照 SKILL.md 重新评估,并在此处更新结果。

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

包含的文件(69)

  • SKILL.md4.5 KB
  • agents/openai.yaml248 B
  • evals/evals.json1.5 KB
  • manifest.yaml3.1 KB
  • README_EN.md3.3 KB
  • README.md2.9 KB
  • references/cn-patent-drafting-guide.md8.0 KB
  • references/corpus-derived-patterns.md3.5 KB
  • references/corpus-pair-audit.md2.9 KB
  • references/disclosure/correction_handler.md2.8 KB
  • references/disclosure/disclosure_builder.md12.1 KB
  • references/disclosure/disclosure_preview.md917 B
  • references/disclosure/disclosure_self_check.md5.9 KB
  • references/disclosure/intake.md943 B
  • references/disclosure/iteration_context.md4.3 KB
  • references/disclosure/merger.md3.4 KB
  • references/disclosure/patent_points_analyzer.md951 B
  • references/disclosure/patent-disclosure-skill-MIT-LICENSE.txt1.0 KB
  • references/disclosure/prior_art_search.md10.4 KB
  • references/disclosure/project_scan.md3.6 KB
  • references/disclosure/template_reference.md9.2 KB
  • references/disclosure/tooling.md16.2 KB
  • references/draft-schema.md9.0 KB
  • references/patent-figure-guide.md2.9 KB
  • requirements.txt121 B
  • scripts/audit_claims.py6.4 KB
  • scripts/build_patent_package.py6.5 KB
  • scripts/disclosure/cnipa_epub_crawler.py10.5 KB
  • scripts/disclosure/cnipa_epub_parse.py8.6 KB
  • scripts/disclosure/cnipa_epub_search.py5.8 KB
  • scripts/disclosure/docx_to_md.py3.7 KB
  • scripts/disclosure/iteration_dialog_log.py3.2 KB
  • scripts/disclosure/math_render.py12.7 KB
  • scripts/disclosure/md_to_docx.py32.2 KB
  • scripts/disclosure/mermaid_render.py15.2 KB
  • scripts/disclosure/package-lock.json84.4 KB
  • scripts/disclosure/package.json279 B
  • scripts/disclosure/pptx_to_md.py4.9 KB
  • scripts/disclosure/requirements-cnipa.txt172 B
  • scripts/extract_pdf_text.py2.3 KB
  • scripts/init_patent_project.py3.1 KB
  • scripts/math_to_omml.py4.8 KB
  • scripts/render_flowchart_svg.py14.3 KB
  • scripts/render_patent_docx.py10.3 KB
  • scripts/validate_patent_draft.py14.6 KB
  • static/core/output-contract.md2.0 KB
  • static/core/principles.md1016 B
  • static/core/workflow.md3.8 KB
  • static/fragments/invention/algorithm-software.md366 B
  • static/fragments/invention/apparatus-system.md288 B
  • static/fragments/invention/mixed.md255 B
  • static/fragments/invention/process-material.md278 B
  • static/fragments/source/mixed-project.md369 B
  • static/fragments/source/pasted-text.md316 B
  • static/fragments/source/pdf-text.md290 B
  • static/fragments/source/scanned-pdf.md272 B
  • static/fragments/task/claim-set.md249 B
  • static/fragments/task/disclosure-analysis.md236 B
  • static/fragments/task/disclosure-iteration.md1005 B
  • static/fragments/task/full-draft.md247 B
  • static/fragments/task/paper-patent-audit.md280 B
  • static/fragments/task/technical-disclosure.md1.5 KB
  • tests/test_audit_claims.py1.6 KB
  • tests/test_inline_math_paren.py1.7 KB
  • tests/test_math_to_omml_superscript.py2.2 KB
  • tests/test_md_to_docx_source_overwrite.py1.4 KB
  • tests/test_mermaid_render.py2.3 KB
  • tests/test_validation_figure_node_ids.py614 B
  • tests/test_validation.py6.0 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

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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