What problem does it solve?
Manually navigating complex USPTO databases for patent and trademark information is time-consuming and error-prone. This Skill automates access to various USPTO APIs, streamlining IP analysis, prior art searches, and portfolio management, allowing users to quickly gain critical insights.
Core Features & Use Cases
- Patent & Trademark Search: Find patents by keywords, inventors, assignees, or classifications, and trademarks by serial/registration number.
- Examination History (PEDS): Retrieve detailed patent prosecution data, including office actions, transaction history, and application status.
- Ownership & Citation Analysis: Track patent and trademark ownership transfers and analyze citation networks (forward/backward citations).
- Use Case: Automatically monitor a competitor's patent portfolio for new filings, analyze their prosecution history to identify potential challenges, and track ownership changes, providing a significant competitive advantage.
Quick Start
Search for machine learning patents using the PatentSearch API
from scripts.patent_search import PatentSearchClient
client = PatentSearchClient()
results = client.search_patents({
"patent_abstract": {"_text_all": ["machine", "learning"]}
})
for patent in results['patents']:
print(f"{patent['patent_number']}: {patent['patent_title']}")
Get trademark status by serial number
from scripts.trademark_client import TrademarkClient
tm_client = TrademarkClient()
tm_data = tm_client.get_trademark_by_serial("87654321") # Replace with actual serial
if tm_data:
print(f"Mark: {tm_data['TradeMarkAppln']['MarkVerbalElementText']}, Status: {tm_data['TradeMarkAppln']['MarkCurrentStatusExternalDescriptionText']}")
