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.
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionuspto-databaseExecute the skills CLI command in your project's root directory to begin installation:
Fetches uspto-database from davila7/claude-code-templates and configures it for Cursor.
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Confirm successful installation by checking the skill directory location:
Restart Cursor to activate uspto-database. Access via /uspto-database in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
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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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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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.
This skill should be used when:
The USPTO provides multiple specialized APIs for different data needs:
PatentSearch API - Modern ElasticSearch-based patent search (replaced legacy PatentsView in May 2025)
https://search.patentsview.org/api/v1/PEDS (Patent Examination Data System) - Patent examination history
uspto-opendata-python Python libraryTSDR (Trademark Status & Document Retrieval) - Trademark data
https://tsdrapi.uspto.gov/ts/cd/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"
This skill includes Python scripts for common operations:
scripts/patent_search.py - PatentSearch API client for searching patentsscripts/peds_client.py - PEDS client for examination historyscripts/trademark_client.py - TSDR client for trademark dataThe PatentSearch API uses a JSON query language with various operators for flexible searching.
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
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
)
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()
{"field": "value"} or {"field": {"_eq": "value"}}_gt, _gte, _lt, _lte, _neq_text_all, _text_any, _text_phrase_begins, _contains_and, _or, _notBest Practice: Use _text_* operators for text fields (more performant than _contains or _begins)
/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)See references/patentsearch_api.md for complete PatentSearch API documentation including:
PEDS provides comprehensive prosecution history including transaction events, status changes, and examination timeline.
uv pip install uspto-opendata-python
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':
✓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
Steps
- 1Install product management skill
- 2Start with user story generation for known feature
- 3Progress to competitive analysis: research 2-3 competitors
- 4Use for roadmap prioritization: apply RICE/ICE scoring
- 5Draft stakeholder communications and refine based on feedback
- 6Build template library for recurring PM tasks
- 7Share 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
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
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4.5★★★★★69 reviews- NNoor Abbas★★★★★Dec 28, 2024
uspto-database reduced setup friction for our internal harness; good balance of opinion and flexibility.
- LLi Rahman★★★★★Dec 20, 2024
Registry listing for uspto-database matched our evaluation — installs cleanly and behaves as described in the markdown.
- LLuis Khanna★★★★★Dec 20, 2024
Solid pick for teams standardizing on skills: uspto-database is focused, and the summary matches what you get after install.
- IIshan Sanchez★★★★★Dec 16, 2024
Solid pick for teams standardizing on skills: uspto-database is focused, and the summary matches what you get after install.
- NNoor Okafor★★★★★Dec 16, 2024
I recommend uspto-database for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- DDaniel Menon★★★★★Dec 8, 2024
uspto-database reduced setup friction for our internal harness; good balance of opinion and flexibility.
- HHarper Taylor★★★★★Dec 4, 2024
uspto-database has been reliable in day-to-day use. Documentation quality is above average for community skills.
- SSophia Gonzalez★★★★★Nov 27, 2024
I recommend uspto-database for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- KKiara Chen★★★★★Nov 19, 2024
I recommend uspto-database for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- LLiam 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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