How to Install the Patent-Disclosure-Skill: A Complete Setup Guide for Claude and Cursor

To install the patent-disclosure-skill, clone the repository into your agent's skills directory (e.g., ~/.claude/skills/ or ~/.cursor/skills/), install Python dependencies with pip install -r requirements.txt, and verify the Playwright browser setup with python tools/shared/browser.py --probe.

The patent-disclosure-skill is an open-source AgentSkills project maintained in the handsomestWei/patent-disclosure-skill repository. It automates invention disclosure drafting, prior art searches, and patent document conversion for AI coding agents. Because it follows the standard AgentSkills layout, installation requires placing files in specific directories, installing Python runtime dependencies, and configuring optional components like headless browsers and CAD environments.

Step 1: Placing the Skill in the Correct Directory

The skill must reside in a recognized skills folder so Claude or Cursor can load the SKILL.md manifest. According to INSTALL.md, the placement depends on your platform:

For Claude-based agents:

• Place the repository under .claude/skills/
• Set the environment variable CLAUDE_SKILL_DIR to point to the folder containing SKILL.md

For Cursor:

• Windows: %USERPROFILE%\.cursor\skills\patent-disclosure-skill\
• macOS/Linux: ~/.cursor/skills/patent-disclosure-skill/
• Project-local: <project-root>/.cursor/skills/patent-disclosure-skill/
• Set CURSOR_SKILL_DIR to the skill root

Clone the repository to the appropriate location:

mkdir -p ~/.claude/skills
git clone https://github.com/handsomestWei/patent-disclosure-skill.git \
    ~/.claude/skills/patent-disclosure-skill

Step 2: Installing Python Dependencies

The repository uses modular requirement files to keep optional dependencies separate. Navigate to the skill root and install the core packages first:

cd ~/.claude/skills/patent-disclosure-skill
pip install -r requirements.txt

The core requirements.txt includes essential libraries such as python-docx, latex2mathml, PyYAML, playwright, mammoth, and python-pptx. For extended functionality, install optional dependency sets:

# CNIPA crawler for prior art searches (Step 5 workflows)

pip install -r tools/crawl/requirements-cnipa.txt

# Office-action (OA) support for mode D workflows

pip install -r tools/oa/requirements-oa.txt

Step 3: Configuring the Browser Environment

The skill relies on Playwright to render Mermaid diagrams and scrape the CNIPA website. After installing Python packages, verify that a system browser is accessible:

python tools/shared/browser.py --probe

If the probe returns ok=true, Playwright can detect your system Chrome or Edge. If not, install the bundled Chromium:

python -m playwright install chromium

The tools/shared/browser.py module handles browser discovery and launch configuration for both diagram generation and web scraping tasks.

Step 4: Optional Components

Depending on your workflow, you may need to configure additional environments.

CAD Environment for STEP File Parsing

If you need to parse mechanical CAD files, prepare the isolated CAD virtual environment. The tools require Python 3.10–3.12 and reside in tools/shared/cad-env:

# Detect existing environment

python tools/shared/cad_venv.py

# Create or activate if missing

python tools/shared/bootstrap_cad_venv.py

The skill will prompt before enabling these tools; they are not installed automatically to keep the footprint minimal.

Obsidian Vault for Reading Mode

For full-featured patent reading and case-library support, configure the Obsidian vault path:

python tools/patent_reader/vault/check_obsidian_env.py --auto-accept

This helper script validates and sets the vault location used by the patent reader mode defined in SKILL.md.

Verifying Your Installation

Confirm that all components are functional by running the browser probe again:

python tools/shared/browser.py --probe

You should see ok=true indicating Playwright can launch. Test the conversion pipeline by rendering a Mermaid diagram to PNG:

python tools/shared/mermaid_render.py -i outputs/case/3.4.mermaid -o outputs/case/3.4.png

Or generate a Word document with math rendering:

python tools/shared/md_to_docx.py -i final.md -o final.docx --math-render

If you installed the CNIPA crawler, test it with:

python tools/crawl/cnipa_epub_search.py --type utility_model "电动汽车"

Summary

• Clone the repository into ~/.claude/skills/ (Claude) or ~/.cursor/skills/ (Cursor) so the agent can locate SKILL.md.
• Install core dependencies via requirements.txt, then add requirements-cnipa.txt or requirements-oa.txt for optional features.
• Verify the Playwright setup using python tools/shared/browser.py --probe and install Chromium if system browsers are unavailable.
• Configure optional components (CAD virtualenv, Obsidian vault) only when needed for STEP parsing or advanced reading workflows.

Frequently Asked Questions

What is the difference between Claude and Cursor installation paths?

Claude requires the skill to live under .claude/skills/, while Cursor supports both user-global paths (~/.cursor/skills/ or %USERPROFILE%\.cursor\skills\) and project-local paths (<project-root>/.cursor/skills/). Both agents use environment variables—CLAUDE_SKILL_DIR and CURSOR_SKILL_DIR—to locate the skill root containing SKILL.md, but Cursor offers more flexibility for per-project customization.

Do I need to install Chromium if I already have Chrome or Edge?

No. If python tools/shared/browser.py --probe returns ok=true, Playwright will use your existing Chrome or Edge installation. You only need to run python -m playwright install chromium if the probe reports that no system browser is discoverable.

What Python version is required for the CAD environment?

The CAD tools in tools/shared/cad-env require Python 3.10–3.12. These tools are isolated in a separate virtual environment created by tools/shared/bootstrap_cad_venv.py to avoid conflicts with the core skill dependencies. The main skill supports other Python versions, but CadQuery-based STEP parsing specifically needs 3.10–3.12.

How do I enable the CNIPA prior art search feature?

Install the crawler dependencies with pip install -r tools/crawl/requirements-cnipa.txt, then ensure Playwright is configured (Step 3). The search functionality is implemented in tools/crawl/cnipa_epub_search.py and requires a working browser environment to scrape the Chinese National Intellectual Property Administration's EPUB archive.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}