patent-disclosure-skill

Generate patent disclosures from project documents with novelty searches.

4.8k|622|Updated Apr 7, 2026
One-click install
npx skills add https://github.com/handsomestWei/patent-disclosure-skill --skill patent-disclosure-skill
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: patent-disclosure-skill
Source: https://github.com/handsomestWei/patent-disclosure-skill/tree/main
Command: npx skills add https://github.com/handsomestWei/patent-disclosure-skill --skill patent-disclosure-skill

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python-docx, mammoth, python-pptx, matplotlib, playwright, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates the full workflow of patent disclosure generation, including scanning project documents, mining patent points, drafting technical disclosures, performing novelty searches, and self-checking for consistency.

Core Features & Use Cases

  • Project Scanning: Reads documents and code with priority, and converts Office files to Markdown before scanning.
  • Patent Point Mining: Discusses and merges candidate points, and selects the best ones.
  • Novelty Search: Prioritizes the China National Intellectual Property Administration (CNIPA) public announcements, and falls back to WebSearch if necessary.
  • Technical Disclosure Drafting: Uses desensitization templates and mermaid diagrams to generate technical disclosures.
  • Delivery Naming: Saves delivered files with a specific naming convention.
  • Self-Check: Checks for logical loops, formula consistency, and parameter consistency.
  • Iteration: Merges or corrects documents and creates new versions with timestamps.
  • Use Case: Imagine you have a project document and want to generate a technical disclosure. Use this Skill to automatically scan the document, mine patent points, perform a novelty search, and generate the disclosure.

Quick Start

Use the patent-disclosure-skill to generate a technical disclosure for the project document 'project-document.pdf'.

Frequently Asked Questions about patent-disclosure-skill

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate patent disclosure generation from project documents?

To automate patent disclosure generation, you can use this Skill to scan project documents, mine patent points, perform novelty searches, and draft technical disclosures with self-checking. It handles Office files by converting them to Markdown before scanning.

How does a novelty search work for mined patent points?

Novelty search works by prioritizing the China National Intellectual Property Administration (CNIPA) public announcements to check mined patent points, falling back to WebSearch if necessary. This ensures your technical disclosures are checked against existing patents.

Can I scan Office files like PPTX and DOCX for patent point mining?

Yes, you can scan Office files like PPTX and DOCX for patent point mining. The Skill uses python-pptx, python-docx, and mammoth to convert Office files into Markdown format before reading and scanning their contents.

Do I need Python libraries installed to generate technical disclosures?

Yes, you need Python libraries installed to generate technical disclosures. This Skill specifically requires python-docx, mammoth, python-pptx, matplotlib, and playwright to handle file conversions, generate diagrams, and perform web searches.

What is the best way to ensure consistency in a technical disclosure draft?

The best way to ensure consistency in a technical disclosure draft is using an automated self-check feature. This Skill checks for logical loops, formula consistency, and parameter consistency, allowing you to iterate and correct documents into new timestamped versions.

Does patent disclosure drafting support generating visual diagrams?

Yes, patent disclosure drafting supports generating visual diagrams. The Skill utilizes matplotlib and mermaid diagrams to create visual representations within your technical disclosures, enhancing the clarity of the desensitized technical content.