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Automate patent invention disclosures with artificial intelligence

The Python-based Patent Disclosure Skill analyzes technical invention drafts to generate technical descriptions, claims, and prior art comparisons in accordance with official patent formats.

Updates

  • October 12, 2026: Stars 10,360 → 11,377.
  • September 27, 2026: Stars 6,058 → 10,360.

What you get

  • Structured patent text generation: Creating the technical field, background, abstract, and detailed description sections of an invention in accordance with standard patent norms.
  • Independent and dependent claim tree: Automatically formulating hierarchical patent claim lists that maximize the scope of legal protection.
  • Prior art gap analysis: Clearly highlighting the technical differences and the inventive step between existing technologies and the invention.
  • Accelerating collaboration with patent attorneys: Saving time and money by transforming engineers' drafts into ready-to-use, organized technical documents for patent attorneys.
  • Multilingual patent terminology support: Compliance with English, Turkish, and international patent office (WIPO, EPO, USPTO) terminology.

Installation

Cloning the repository and installing dependencies
git clone https://github.com/handsomestWei/patent-disclosure-skill.git
cd patent-disclosure-skill
pip install -r requirements.txt

Running it

Initiating patent analysis and disclosure generation
python run_skill.py --input bulus_taslagi.txt --output patent_disclosure.md

Technical architecture and working principle

  • Technical Invention Decomposition Engine: Identifies key inputs, outputs, and methodology in software, hardware, or chemical process descriptions.
  • Claim Syntax Validator: A legal language analyzer that checks for vague expressions and formal errors in claims.
  • Template and Markdown Export: Saving the document in a standard sectioned Markdown format for use in official patent applications.

Patent analysis workflows and claim preparation

  • Converting Software Algorithms into Patentable Formats: Deriving method and system descriptions acceptable to patent authorities from code and architectural diagrams.
  • Defense Against Office Actions: Drafting responses that list the distinctive features of an invention in response to objections from patent examiners.
  • Intellectual Property Portfolio Audit: Early mapping of the inventive steps within in-house technological projects that hold patent potential.

If you don't write code

Paste this into your AI agent (Claude Code · Codex · Antigravity)

I want to prepare a formal invention disclosure text for a distributed database caching algorithm I developed using the patent disclosure skill. Could you explain step-by-step how I can generate independent claims, the technical field of the invention, and the differences from prior art by providing the algorithm's flow as input?

Repository: https://github.com/handsomestWei/patent-disclosure-skill. Follow the official instructions in the README of this repository for setup and execution.

Before starting, check which OS we are on and if the necessary tools (e.g., Python, Node.js, Git, Docker) are installed. Install any missing ones step-by-step according to this system.

Create a new, empty folder to work in. Do not touch any files outside this folder and do not delete anything. Tell me what you are going to do in one sentence before running each command.

Tell me what I should see on the screen at the end of each step. If an error occurs, I will paste the error message to you exactly as it is, and we will fix it together.

Frequently asked questions

  • Does this tool replace a registered patent attorney? No. Patent Disclosure Skill is a preliminary preparation and productivity tool that helps engineers draft their inventions and prepare them for attorneys; legal filings must be handled by an attorney.
  • Which LLM models does it work with? It can be configured to work with Claude 3.5 Sonnet, GPT-4o, or local open-weight models (Qwen, Llama 3).
  • Will my confidential technical secrets leak to the internet? When running with a local LLM (Ollama or vLLM), all patent analyses are performed entirely on your local computer, and no data leaves your machine.
  • Can it interpret patent drawings and flowcharts? When multimodal models are connected, it can also analyze system architecture and block diagram images and transcribe them into text.

Related dictionary terms

Who it is forPatent attorneys, intellectual property managers, R&D engineers, and inventors.
LicenseMIT (Free open source license)
FrameworkPython-Based Patent Agent Skill
PlatformsLinux, macOS, Windows

Links

TreScout did not build this tool · we found it in GitHub trends and wrote it up. This page describes the repository as of 2026-08-31: The star count and our text belong to that day, the repository may have changed since. Check the repository link for the current state. The introductory text was prepared with AI from the repository's own documentation, and this page was machine-translated from the Turkish original · the Turkish version prevails.