Refactor high-complexity React components in Dify frontend. Use when `pnpm analyze-component...
npx skills add RobThePCGuy/Claude-Patent-Creator --skill "prior-art-search"
Install specific skill from multi-skill repository
# Description
Systematic 7-step methodology for comprehensive patent prior art searches and patentability assessments using BigQuery and CPC classification
# SKILL.md
name: prior-art-search
description: Systematic 7-step methodology for comprehensive patent prior art searches and patentability assessments using BigQuery and CPC classification
tools: Bash, Read, Write
model: sonnet
Prior Art Search Skill
Systematic 7-step methodology for comprehensive patent prior art searches and patentability assessments.
When to Use
Invoke this skill when users ask to:
- Conduct prior art search for an invention
- Assess patentability of an idea
- Perform freedom-to-operate analysis
- Find blocking patents
- Research patent landscapes
- Prepare for patent filing
What This Skill Does
Implements a professional 7-step prior art search methodology combining:
- Keyword searches across 76M+ patents (BigQuery)
- CPC classification searches
- USPTO API searches
- Timeline analysis
- Patentability assessment
- IDS (Information Disclosure Statement) preparation
The 7-Step Methodology
Step 1: Invention Definition (2-3 min)
Goal: Extract key features and define innovation scope
Process:
1. Interview user about invention
2. Extract core technical elements
3. Identify novel features
4. List all components/steps
5. Define search scope
Output: Structured invention summary with key features
Questions to Ask:
- What problem does this solve?
- What are the key components/steps?
- What makes this different from existing solutions?
- What is the core innovation?
Step 2: Keyword Strategy (2-3 min)
Goal: Develop comprehensive search keyword list
Process:
1. Primary keywords from invention
2. Synonyms and variations
3. Technical terminology
4. Industry-specific terms
5. Boolean search strings
Output: Keyword search strategy document
Example:
Primary: blockchain authentication
Synonyms: distributed ledger verification, cryptographic authentication
Technical: public key infrastructure, digital signature
Related: decentralized identity, trustless verification
Searches:
- "blockchain AND (authentication OR verification)"
- "(distributed ledger) AND (identity OR credential)"
- "cryptographic AND (login OR access control)"
Step 3: Broad Keyword Search (3-5 min)
Goal: Cast wide net to find relevant patents
Process:
1. Run keyword searches on BigQuery
2. Review top 20-30 results per query
3. Identify most relevant patents
4. Refine keyword strategy based on results
5. Document relevant patents found
Code:
from python.bigquery_search import BigQueryPatentSearch
searcher = BigQueryPatentSearch()
results = searcher.search_patents(
query="blockchain authentication",
limit=30,
country="US",
start_year=2015 # Look back 5-10 years
)
Output: List of 10-20 potentially relevant patents
Step 4: CPC Code Identification (2-3 min)
Goal: Find relevant classification codes
Process:
1. Extract CPC codes from relevant patents found in Step 3
2. Analyze CPC code descriptions
3. Identify primary classification areas
4. Select 3-5 most relevant CPC codes
5. Note CPC hierarchies
Common CPC Categories:
- G06F: Computing/data processing
- H04L: Digital communication/networks
- G06Q: Business methods
- H04W: Wireless communication
- G06N: AI/neural networks
- G06T: Image processing
Output: List of relevant CPC codes with descriptions
Step 5: Deep CPC Search (5-10 min)
Goal: Comprehensive search within classifications
Process:
1. Search each CPC code identified
2. Review 50-100 patents per CPC code
3. Read abstracts and claims of top matches
4. Document closest prior art
5. Note key differences from invention
Code:
results = searcher.search_by_cpc(
cpc_code="G06F21/", # Security arrangements
limit=100,
country="US"
)
Output: Comprehensive list of potentially blocking patents
Step 6: Timeline Analysis (2-3 min)
Goal: Understand technology evolution
Process:
1. Filter results by date ranges
2. Identify filing trends over time
3. Find recent developments (last 2 years)
4. Check priority dates
5. Note technology progression
Code:
# Search by year ranges
recent = searcher.search_patents(query, start_year=2022, end_year=2024)
older = searcher.search_patents(query, start_year=2015, end_year=2021)
Output: Timeline showing technology development
Step 7: Patentability Report (5-10 min)
Goal: Professional assessment and recommendations
Process:
1. Analyze top 10 closest prior art
2. Assess novelty (35 USC 102)
3. Assess non-obviousness (35 USC 103)
4. Rank prior art by relevance
5. Provide claim strategy recommendations
6. Generate IDS list
Output: Comprehensive patentability report
Report Format
# PRIOR ART SEARCH REPORT
## Executive Summary
- Invention: [Brief description]
- Search Date: [Date]
- Searcher: Claude Patent Creator
- Databases: BigQuery (76M+ patents), USPTO API
- Time Period: [Year range]
## Patentability Assessment
### Novelty (35 USC 102)
[Assessment of whether invention is novel]
Score: [High/Medium/Low]
Analysis:
- No exact matches found
- Closest prior art: US10123456
- Key differences: [List]
### Non-Obviousness (35 USC 103)
[Assessment of whether invention is non-obvious]
Score: [High/Medium/Low]
Analysis:
- Combinations considered: [List]
- Motivation to combine: [Analysis]
- Unexpected results: [If any]
## Top 10 Most Relevant Prior Art
### 1. US10123456B2 - [Title] (95% Relevance)
**Assignee**: Example Corp
**Filed**: 2018-03-15
**Granted**: 2019-09-30
**CPC**: G06F21/31, H04L29/06
**Summary**: [Brief abstract]
**Similarities**:
- Uses blockchain for authentication
- Employs public key cryptography
- Distributed verification
**Differences**:
- Does not use [novel feature 1]
- Lacks [novel feature 2]
- Different approach to [aspect]
**Relevance**: High - core technology overlap
---
[Continue for top 10 patents...]
## Search Methodology
### Keywords Used
- Primary: blockchain, authentication, distributed ledger
- Synonyms: cryptographic verification, decentralized identity
- Technical: public key infrastructure, digital signature
### CPC Codes Searched
- G06F21/31 (Authentication)
- H04L29/06 (Security arrangements)
- G06Q20/40 (Payment authentication)
### Databases
- Google BigQuery: 247 results reviewed
- USPTO API: 89 results reviewed
- Total patents analyzed: 336
- Relevant patents identified: 47
- Top prior art selected: 10
## Claim Strategy Recommendations
### Recommended Approach
1. **Focus on novel aspects**: [Specific features]
2. **Claim breadth**: Start broad, add dependent claims
3. **Avoid prior art**: Distinguish from US10123456 by [...]
### Suggested Independent Claim Language
A system for [invention], comprising:
[novel element 1];
[novel element 2];
wherein [novel relationship/function]
### Dependent Claim Opportunities
- Specific implementations of [feature]
- Combinations with [technology]
- Variations in [parameter/configuration]
## IDS (Information Disclosure Statement) List
Patents to be disclosed to USPTO:
1. US10123456B2 - [Title]
2. US10234567A1 - [Title]
3. US10345678B1 - [Title]
4. US10456789A1 - [Title]
5. US10567890B2 - [Title]
6. EP3123456A1 - [Title]
7. WO2019/123456 - [Title]
8. US2020/0123456A1 - [Title]
9. US10678901B2 - [Title]
10. US10789012A1 - [Title]
## Conclusion
**Patentability**: [High/Medium/Low]
**Rationale**:
[Summary of why invention is or is not patentable]
**Recommended Next Steps**:
1. [Action item 1]
2. [Action item 2]
3. [Action item 3]
Integration Points
This skill integrates with:
- BigQuery Patent Search skill (Step 3, 5, 6)
- MPEP Search skill (For legal guidance)
- Patent Claims Analyzer (For claim drafting)
Required Data Access
- Google Cloud BigQuery (76M+ patents)
- USPTO API (optional, for additional coverage)
- Internet access for patent retrieval
Estimated Time
- Quick Search (Steps 1-3): 10-15 minutes
- Thorough Search (Steps 1-6): 25-35 minutes
- Complete Report (All 7 steps): 40-60 minutes
Tools Available
- Bash: To run Python searches
- Write: To save report and findings
- Read: To load invention descriptions
- Grep: To search through results
# Supported AI Coding Agents
This skill is compatible with the SKILL.md standard and works with all major AI coding agents:
Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.