patent-claims-analyzer

robthepcguy/claude-patent-creator · updated Apr 10, 2026

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$npx skills add https://github.com/robthepcguy/claude-patent-creator --skill patent-claims-analyzer
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summary

Automated analysis of patent claims for USPTO compliance with 35 USC 112(b) requirements.

skill.md

Patent Claims Analyzer Skill

Automated analysis of patent claims for USPTO compliance with 35 USC 112(b) requirements.

When to Use

Invoke this skill when users ask to:

  • Review patent claims for definiteness
  • Check antecedent basis in claims
  • Analyze claim structure
  • Find claim drafting issues
  • Validate claims before filing
  • Fix USPTO office action issues related to claims

What This Skill Does

Performs comprehensive automated analysis:

  1. Antecedent Basis Checking:

    • Finds terms used without prior introduction
    • Detects missing "a/an" before first use
    • Identifies improper "said/the" before first use
    • Tracks term references across claims
  2. Definiteness Analysis (35 USC 112(b)):

    • Identifies subjective/indefinite terms
    • Detects relative terms without reference
    • Finds ambiguous claim language
    • Checks for clear claim boundaries
  3. Claim Structure Validation:

    • Parses independent vs. dependent claims
    • Validates claim dependencies
    • Checks claim numbering
    • Identifies claim type (method, system, etc.)
  4. Issue Categorization:

    • Critical: Must fix before filing
    • Important: May cause rejection
    • Minor: Best practice improvements

Required Data

This skill uses the automated claims analyzer from: Location: ${CLAUDE_PLUGIN_ROOT}/python\claims_analyzer.py

How to Use

When this skill is invoked:

  1. Load the claims analyzer:

    import sys
    sys.path.insert(0, os.path.join(os.environ.get('CLAUDE_PLUGIN_ROOT', '.'), 'python'))
    from python.claims_analyzer import ClaimsAnalyzer
    
    analyzer = ClaimsAnalyzer()
    
  2. Analyze claims:

    claims_text = """
    1. A system comprising:
        a processor;
        a memory; and
        said processor configured to...
    """
    
    results = analyzer.analyze_claims(claims_text)
    
  3. Present analysis:

    • Show compliance score (0-100)
    • List issues by severity (critical, important, minor)
    • Provide MPEP citations for each issue
    • Suggest specific fixes

Analysis Output Structure

{
    "claim_count": 20,
    "independent_count": 3,
    "dependent_count": 17,
    "compliance_score": 85,  # 0-100
    "total_issues": 12,
    "critical_issues": 2,
    "important_issues": 7,
    "minor_issues": 3,
    "issues": [
        {
            "category": "antecedent_basis",
            "severity": "critical",
            "claim_number": 1,
            "term": "said processor",
            "description": "Term 'processor' used with 'said' before first introduction",
            "mpep_cite": "MPEP 2173.05(e)",
            "suggestion": "Change 'said processor' to 'the processor' or introduce with 'a processor' first"
        },
        # ... more issues
    ]
}

Common Issues Detected

  1. Antecedent Basis Errors:

    • Using "said/the" before "a/an" introduction
    • Terms appearing in dependent claims not in parent
    • Missing antecedent in claim body
  2. Definiteness Issues:

    • Subjective terms: "substantially", "about", "approximately"
    • Relative terms: "large", "small", "thin"
    • Ambiguous language: "and/or", "optionally"
  3. Structure Issues:

    • Means-plus-function without adequate structure
    • Improper claim dependencies
    • Missing preamble or transition

Presentation Format

Present analysis as:

CLAIMS ANALYSIS REPORT
======================

Summary:
- Total Claims: 20 (3 independent, 17 dependent)
- Compliance Score: 85/100
- Issues Found: 12 (2 critical, 7 important, 3 minor)

CRITICAL ISSUES (Must Fix):

[Claim 1] Antecedent Basis Error
  Issue: Term 'processor' used with 'said' before introduction
  Location: "said processor configured to..."
  MPEP: 2173.05(e)
  Fix: Change to 'the processor' or introduce with 'a processor' first

[Claim 5] Indefinite Term
  Issue: Subjective term 'substantially' without definition
  Location: "substantially similar to..."
  MPEP: 2173.05(b)
  Fix: Define 'substantially' in specification or use objective criteria

IMPORTANT ISSUES:
...

MINOR ISSUES:
...

Integration with MPEP

For each issue, the skill can:

  1. Search MPEP for relevant guidance
  2. Provide specific MPEP section citations
  3. Show examiner guidance on similar issues
  4. Suggest fixes based on USPTO practice

Tools Available

  • Read: To load claims from files
  • Bash: To run Python analyzer
  • Write: To save analysis reports
how to use patent-claims-analyzer

How to use patent-claims-analyzer on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add patent-claims-analyzer
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/robthepcguy/claude-patent-creator --skill patent-claims-analyzer

The skills CLI fetches patent-claims-analyzer from GitHub repository robthepcguy/claude-patent-creator and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/patent-claims-analyzer

Reload or restart Cursor to activate patent-claims-analyzer. Access the skill through slash commands (e.g., /patent-claims-analyzer) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.736 reviews
  • Pratham Ware· Dec 28, 2024

    patent-claims-analyzer fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Chaitanya Patil· Dec 20, 2024

    Keeps context tight: patent-claims-analyzer is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Mateo Bhatia· Dec 20, 2024

    Registry listing for patent-claims-analyzer matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Naina Bhatia· Dec 8, 2024

    I recommend patent-claims-analyzer for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Aisha Rahman· Nov 27, 2024

    patent-claims-analyzer reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Piyush G· Nov 11, 2024

    patent-claims-analyzer has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Mateo Mehta· Nov 11, 2024

    Useful defaults in patent-claims-analyzer — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Meera Singh· Oct 18, 2024

    Registry listing for patent-claims-analyzer matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Shikha Mishra· Oct 2, 2024

    Solid pick for teams standardizing on skills: patent-claims-analyzer is focused, and the summary matches what you get after install.

  • Hassan Chawla· Oct 2, 2024

    I recommend patent-claims-analyzer for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

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