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nature-paper-to-patent

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 revise a Chinese technical disclosure (技术交底书), run prior-art comparison, convert Office project materials, map every claimed feature to source evidence, preserve core formulas as editable Office Math, generate claim-aligned flowcharts and methodology figures, compare a paper with an existing patent, audit support and consistency, or deliver Chinese DOCX patent/disclosure files.

DeepseekModel Curated skill Quality Excellent · 90 v1.0.0

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https://deepseekmodel.com/api/download.php?id=yuan1z0825-nature-skills-skills-nature-paper-to-patent-skill-md&format=skill
Download .skill Standard format with system_prompt and model_config, ready for any agent framework
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name nature-paper-to-patent description 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 revise a Chinese technical disclosure (技术交底书), run prior-art comparison, convert Office project materials, map every claimed feature to source evidence, preserve core formulas as editable Office Math, generate claim-aligned flowcharts and methodology figures, compare a paper with an existing patent, audit support and consistency, or deliver Chinese DOCX patent/disclosure files. 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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Field Description
formatFormat tag (skill/v1)
skill_idUnique skill ID
nameSkill name
versionVersion
descriptionDescription
categoryCategories (array)
trigger_wordsTrigger words
tagsTags
sourceSource
source_urlSource URL (this page)
exported_atExported at (set per download)
system_promptSystem prompt body
model_configModel config: provider / model / temperature / max_tokens / top_p
examplesExamples
install_guideImport guide for Coze / Dify / Claude / custom frameworks
The same skill can be exported in different platform formats.
.skill Standard format with system_prompt and model_config, ready for any agent framework Download
.skillpro Enhanced format with scripts, tools, dependencies and hooks Download
.json Plain JSON export with system_prompt and model parameters only Download
Coze Markdown with frontmatter, for Coze platform import Download
Dify Dify DSL, import directly after creating an app Download

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