跨多个来源检索学术文献、核对引文并转换参考文献文件;可使用MeSH设计PubMed检索式,也可区分独立他引与自引,整理引用者及引用语境。
- 跨多个来源检索文献
- 核对文档中的引文信息
- 用MeSH设计PubMed检索式
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。
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。
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。
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)。
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。
安装前可以查看交给 AI 代理的指令内容。
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:
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.
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Never infer inventorship, ownership, unpublished implementation details,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.
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.
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跨多个来源检索学术文献、核对引文并转换参考文献文件;可使用MeSH设计PubMed检索式,也可区分独立他引与自引,整理引用者及引用语境。
在指定的Nature系列或CNS相关期刊范围内查找论文,核对摘要或出版社页面,将文献对应到稿件中的具体论点,并导出经核实、可导入文献管理软件的参考信息。
起草或检查论文的数据与代码可用性声明,整理数据来源、存储位置、访问限制、标识符和正式引用,并核对有助于发现与复用数据的元数据。
通过开放获取、出版社 API 或机构授权渠道获取学术论文全文和补充材料。它会为每篇文献选择获取途径,并记录文件格式、来源和下载结果。
把实验照片、音频和文字整理成带结构化元数据的 Markdown 日志,分配实验编号和样品批次编号,并归档原始附件;还可选接入飞书群消息或 Obsidian。
使用Python或R创建、修改并导出论文科学图,检查多面板对齐、文字和元素重叠。也可制作可编辑的矢量示意图,以及经明确要求生成的图形摘要。