
prior-art-search
Systematic 7-step methodology for comprehensive patent prior art searches and patentability assessments using BigQuery and CPC classification
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/robthepcguy/claude-patent-creator --skill prior-art-search- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads prior-art-search automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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 100M+ 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:
- Interview user about invention
- Extract core technical elements
- Identify novel features
- List all components/steps
- 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:
- Primary keywords from invention
- Synonyms and variations
- Technical terminology
- Industry-specific terms
- Synonym sets to run as separate searches
Query syntax (important): the keyword search splits a query into terms and
requires every term to appear (AND), each matching the title, abstract, or
claims (results are ranked by relevance, title hits weighted highest). It does
not parse Boolean operators — AND/OR/parentheses are ignored. So:
- Use plain space-separated terms for the AND set:
blockchain authentication. - Wrap a phrase in double quotes to require it verbatim:
"distributed ledger". - For OR / synonyms, run separate searches and merge the results — don't put
ORin one query.
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 (run each separately, then merge/dedupe):
- blockchain authentication
- "distributed ledger" verification
- cryptographic authentication
- "public key infrastructure" signature
Step 3: Broad Keyword Search (3-5 min)
Goal: Cast wide net to find relevant patents
Process:
- Run keyword searches on BigQuery
- Review top 20-30 results per query
- Identify most relevant patents
- Refine keyword strategy based on results
- Document relevant patents found
Code:
from mcp_server.bigquery_search import BigQueryPatentSearch
searcher = BigQueryPatentSearch()
results = searcher.search_by_keywords(
query="blockchain authentication", # terms AND-matched, ranked by relevance
limit=30,
country="US",
start_year=2015, # filing year; 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:
- Extract CPC codes from relevant patents found in Step 3
- Analyze CPC code descriptions
- Identify primary classification areas
- Select 3-5 most relevant CPC codes
- 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:
- Search each CPC code identified
- Review 50-100 patents per CPC code
- Read abstracts and claims of top matches
- Document closest prior art
- 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:
- Filter results by date ranges
- Identify filing trends over time
- Find recent developments (last 2 years)
- Check priority dates
- Note technology progression
Code:
# Search by year ranges
recent = searcher.search_by_keywords(query, start_year=2022, end_year=2024)
older = searcher.search_by_keywords(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:
- Analyze top 10 closest prior art
- Assess novelty (35 USC 102)
- Assess non-obviousness (35 USC 103)
- Rank prior art by relevance
- Provide claim strategy recommendations
- 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 (100M+ 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 (100M+ 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
FAQ
What does the prior-art-search skill do?
Systematic 7-step methodology for comprehensive patent prior art searches and patentability assessments using BigQuery and CPC classification
How do I install prior-art-search?
Run npx skills add https://github.com/robthepcguy/claude-patent-creator --skill prior-art-search in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/prior-art-search/ (personal) or .claude/skills/prior-art-search/ (project).
Which AI agents can use prior-art-search?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is prior-art-search safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains prior-art-search?
It is published by robthepcguy in robthepcguy/claude-patent-creator. It has 247 recorded installs.
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