uspto-database

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$npx skills add https://github.com/davila7/claude-code-templates --skill uspto-database
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summary

USPTO provides specialized APIs for patent and trademark data. Search patents by keywords/inventors/assignees, retrieve examination history via PEDS, track assignments, analyze citations and office actions, access TSDR for trademarks, for IP analysis and prior art searches.

skill.md

USPTO Database

Overview

USPTO provides specialized APIs for patent and trademark data. Search patents by keywords/inventors/assignees, retrieve examination history via PEDS, track assignments, analyze citations and office actions, access TSDR for trademarks, for IP analysis and prior art searches.

When to Use This Skill

This skill should be used when:

  • Patent Search: Finding patents by keywords, inventors, assignees, classifications, or dates
  • Patent Details: Retrieving full patent data including claims, abstracts, citations
  • Trademark Search: Looking up trademarks by serial or registration number
  • Trademark Status: Checking trademark status, ownership, and prosecution history
  • Examination History: Accessing patent prosecution data from PEDS (Patent Examination Data System)
  • Office Actions: Retrieving office action text, citations, and rejections
  • Assignments: Tracking patent/trademark ownership transfers
  • Citations: Analyzing patent citations (forward and backward)
  • Litigation: Accessing patent litigation records
  • Portfolio Analysis: Analyzing patent/trademark portfolios for companies or inventors

USPTO API Ecosystem

The USPTO provides multiple specialized APIs for different data needs:

Core APIs

  1. PatentSearch API - Modern ElasticSearch-based patent search (replaced legacy PatentsView in May 2025)

    • Search patents by keywords, inventors, assignees, classifications, dates
    • Access to patent data through June 30, 2025
    • 45 requests/minute rate limit
    • Base URL: https://search.patentsview.org/api/v1/
  2. PEDS (Patent Examination Data System) - Patent examination history

    • Application status and transaction history from 1981-present
    • Office action dates and examination events
    • Use uspto-opendata-python Python library
    • Replaced: PAIR Bulk Data (PBD) - decommissioned
  3. TSDR (Trademark Status & Document Retrieval) - Trademark data

    • Trademark status, ownership, prosecution history
    • Search by serial or registration number
    • Base URL: https://tsdrapi.uspto.gov/ts/cd/

Additional APIs

  1. Patent Assignment Search - Ownership records and transfers
  2. Trademark Assignment Search - Trademark ownership changes
  3. Enriched Citation API - Patent citation analysis
  4. Office Action Text Retrieval - Full text of office actions
  5. Office Action Citations - Citations from office actions
  6. Office Action Rejection - Rejection reasons and types
  7. PTAB API - Patent Trial and Appeal Board proceedings
  8. Patent Litigation Cases - Federal district court litigation data
  9. Cancer Moonshot Data Set - Cancer-related patents

Quick Start

API Key Registration

All USPTO APIs require an API key. Register at: https://account.uspto.gov/api-manager/

Set the API key as an environment variable:

export USPTO_API_KEY="your_api_key_here"

Helper Scripts

This skill includes Python scripts for common operations:

  • scripts/patent_search.py - PatentSearch API client for searching patents
  • scripts/peds_client.py - PEDS client for examination history
  • scripts/trademark_client.py - TSDR client for trademark data

Task 1: Searching Patents

Using the PatentSearch API

The PatentSearch API uses a JSON query language with various operators for flexible searching.

Basic Patent Search Examples

Search by keywords in abstract:

from scripts.patent_search import PatentSearchClient

client = PatentSearchClient()

# Search for machine learning patents
results = client.search_patents({
    "patent_abstract": {"_text_all": ["machine", "learning"]}
})

for patent in results['patents']:
    print(f"{patent['patent_number']}: {patent['patent_title']}")

Search by inventor:

results = client.search_by_inventor("John Smith")

Search by assignee/company:

results = client.search_by_assignee("Google")

Search by date range:

results = client.search_by_date_range("2024-01-01", "2024-12-31")

Search by CPC classification:

results = client.search_by_classification("H04N")  # Video/image tech

Advanced Patent Search

Combine multiple criteria with logical operators:

results = client.advanced_search(
    keywords=["artificial", "intelligence"],
    assignee="Microsoft",
    start_date="2023-01-01",
    end_date="2024-12-31",
    cpc_codes=["G06N", "G06F"]  # AI and computing classifications
)

Direct API Usage

For complex queries, use the API directly:

import requests

url = "https://search.patentsview.org/api/v1/patent"
headers = {
    "X-Api-Key": "YOUR_API_KEY",
    "Content-Type": "application/json"
}

query = {
    "q": {
        "_and": [
            {"patent_date": {"_gte": "2024-01-01"}},
            {"assignee_organization": {"_text_any": ["Google", "Alphabet"]}},
            {"cpc_subclass_id": ["G06N", "H04N"]}
        ]
    },
    "f": ["patent_number", "patent_title", "patent_date", "inventor_name"],
    "s": [{"patent_date": "desc"}],
    "o": {"per_page": 100, "page": 1}
}

response = requests.post(url, headers=headers, json=query)
results = response.json()

Query Operators

  • Equality: {"field": "value"} or {"field": {"_eq": "value"}}
  • Comparison: _gt, _gte, _lt, _lte, _neq
  • Text search: _text_all, _text_any, _text_phrase
  • String matching: _begins, _contains
  • Logical: _and, _or, _not

Best Practice: Use _text_* operators for text fields (more performant than _contains or _begins)

Available Patent Endpoints

  • /patent - Granted patents
  • /publication - Pregrant publications
  • /inventor - Inventor information
  • /assignee - Assignee information
  • /cpc_subclass, /cpc_at_issue - CPC classifications
  • /uspc - US Patent Classification
  • /ipc - International Patent Classification
  • /claims, /brief_summary_text, /detail_description_text - Text data (beta)

Reference Documentation

See references/patentsearch_api.md for complete PatentSearch API documentation including:

  • All available endpoints
  • Complete field reference
  • Query syntax and examples
  • Response formats
  • Rate limits and best practices

Task 2: Retrieving Patent Examination Data

Using PEDS (Patent Examination Data System)

PEDS provides comprehensive prosecution history including transaction events, status changes, and examination timeline.

Installation

uv pip install uspto-opendata-python

Basic PEDS Usage

Get application data:

from scripts.peds_client import PEDSHelper

helper = PEDSHelper()

# By application number
app_data = helper.get_application("16123456")
print(f"Title: {app_data['title']}")
print(f"Status: {app_data['app_status']}")

# By patent number
patent_data = helper.get_patent("11234567")

Get transaction history:

transactions = helper.get_transaction_history("16123456")

for trans in transactions:
    print(f"{trans['date']}: {trans['code']} - {trans['description']}")

Get office actions:

office_actions = helper.get_office_actions("16123456")

for oa in office_actions:
    if oa['code'] == 'CTNF':
        print(f"Non-final rejection: {oa['date']}")
    elif oa['code'] == 'CTFR':
how to use uspto-database

How to use uspto-database 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 uspto-database
2

Execute installation command

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

$npx skills add https://github.com/davila7/claude-code-templates --skill uspto-database

The skills CLI fetches uspto-database from GitHub repository davila7/claude-code-templates 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/uspto-database

Reload or restart Cursor to activate uspto-database. Access the skill through slash commands (e.g., /uspto-database) 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

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

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

Ratings

4.569 reviews
  • Noor Abbas· Dec 28, 2024

    uspto-database reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Li Rahman· Dec 20, 2024

    Registry listing for uspto-database matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Luis Khanna· Dec 20, 2024

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

  • Ishan Sanchez· Dec 16, 2024

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

  • Noor Okafor· Dec 16, 2024

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

  • Daniel Menon· Dec 8, 2024

    uspto-database reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Harper Taylor· Dec 4, 2024

    uspto-database has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Sophia Gonzalez· Nov 27, 2024

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

  • Kiara Chen· Nov 19, 2024

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

  • Liam Bansal· Nov 11, 2024

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

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