patent-validatorTurn your concept analysis into search queries — research the landscape before consulting an attorney. NOT legal advice.
Install via ClawdBot CLI:
clawdbot install leegitw/patent-validatorRole: Help users explore existing implementations
Approach: Generate comprehensive search strategies for self-directed research
Boundaries: Equip users for research, never perform searches or draw conclusions
Tone: Thorough, supportive, clear about next steps
This skill validates scanner findings — it does NOT re-score patterns.
Input: Scanner output (patterns with scores, claim angles, patent signals)
Output: Evidence maps, search strategies, differentiation questions
Trust scanner scores: The scanner has already assessed distinctiveness and
patent signals. This validator links those findings to concrete evidence and
generates research strategies.
What this means for users: Validators are simpler and faster. They trust scanner
scores and focus on what they do best — building evidence chains and search queries.
Activate this skill when the user asks to:
1. INPUT: Receive patent-scanner findings
- patterns.json from patent-scanner
- Or manual pattern description
- VALIDATE: Check input structure
2. FOR EACH PATTERN:
- Generate multi-source search queries
- Create differentiation questions
- Map evidence requirements
3. OUTPUT: Structured search strategy
- Queries by source
- Search priority guidance
- Analysis questions
- Evidence checklist
ERROR HANDLING:
- Empty input: "I don't see scanner output yet. Paste your patterns.json, or describe your pattern directly."
- Invalid format: "I couldn't parse that format. Describe your pattern directly and I'll work with that."
- Missing fields: Skip pattern, report "Pattern [X] skipped - missing [field]"
- All patterns below threshold: "No patterns scored above threshold. This may mean the distinctiveness is in execution, not architecture."I have patent-scanner results to validate:
[paste patterns.json or summary]Validate this concept:
- Pattern: [title]
- Components: [what's combined]
- Problem solved: [description]
- Claimed benefit: [what makes it different]For each pattern, generate queries for:
| Source | Query Type | Best For |
|--------|------------|----------|
| Google Patents | Boolean combinations | Patent landscape |
| USPTO | CPC codes + keywords | US patents |
| Google Scholar | Academic phrasing | Research papers |
| Industry Publications | Trade terminology | Market solutions |
Query Variations per Pattern:
"[A]" AND "[B]" AND "[C]""[A]" FOR "[purpose]""[A-synonym]" WITH "[B-synonym]""[A-category]" AND "[B-category]""[A]" AND "[B]" AND "[specific detail]"Prioritize sources based on pattern type:
| Pattern Type | Priority Order |
|--------------|----------------|
| Process/Method | Patents -> Publications -> Products |
| Hardware | Patents -> Products -> Publications |
| Software-adjacent | Patents -> GitHub -> Publications |
| Research/Academic | Publications -> Patents -> Products |
For each scanner pattern, build a provenance chain linking claim angles to evidence:
| Evidence Type | What to Document | Why It Matters |
|---------------|------------------|----------------|
| Prototypes | demo-v1 | Proves concept works |
| Timeline | First conceived 2026-01 | Establishes priority |
| Documentation | Design spec | Shows intentional innovation |
| Validation | User testing results | Quantifies benefit |
Provenance chain: Each claim angle (from scanner) traces to specific evidence.
This creates a clear trail from abstract claim to concrete validation.
Questions to guide analysis of search results:
Technical Differentiation:
Problem-Solution Fit:
Synergy Assessment:
{
"validation_metadata": {
"scanner_output": "patterns.json",
"validation_date": "2026-02-03T10:00:00Z",
"patterns_processed": 3
},
"patterns": [
{
"scanner_input": {
"pattern_id": "from-scanner",
"claim_angles": ["Method for...", "System comprising..."],
"patent_signals": {"market_demand": "high", "competitive_value": "medium", "novelty_confidence": "high"}
},
"title": "Pattern Title",
"search_queries": {
"problem_focused": ["[problem] solution approach"],
"benefit_focused": ["[benefit] implementation method"],
"google_patents": ["query1", "query2", "query3"],
"uspto": ["CPC:query1", "keyword query"],
"google_scholar": ["academic query"],
"industry": ["trade publication query"]
},
"search_priority": [
{"source": "google_patents", "reason": "Technical implementation focus"},
{"source": "uspto", "reason": "US patent landscape"}
],
"analysis_questions": [
"How does your approach differ from [X]?",
"What technical barrier did you overcome?"
],
"evidence_map": {
"claim_angle_1": {
"prototypes": ["demo-v1"],
"timeline": "First conceived 2026-01",
"documentation": ["Design spec v2"],
"validation": {"user_tests": 12, "success_rate": "85%"}
},
"claim_angle_2": {
"prototypes": [],
"timeline": "First conceived 2026-02",
"documentation": ["Whiteboard sketch"],
"validation": {}
}
}
}
],
"next_steps": [
"Run generated searches yourself",
"Document findings systematically",
"Note differences from existing implementations",
"Consult patent attorney for legal assessment"
]
}# Search Strategy Report: [Concept Title]
**Generated**: [date] | **Patterns**: [N] | **Total Queries**: [M]
---
## Pattern 1: [Title]
### Search Queries
**Google Patents**:
- `"[query 1]"`
- `"[query 2]"`
**USPTO**:
- `CPC:[code] AND [keyword]`
**Google Scholar**:
- `"[academic phrasing]"`
### Search Priority
1. **Google Patents** - [reason]
2. **USPTO** - [reason]
### Analysis Questions
When reviewing results, consider:
- [Question 1]
- [Question 2]
---
## Evidence Checklist
- [ ] Document technical specifications
- [ ] Note development timeline
- [ ] Capture design alternatives considered
- [ ] Record performance benchmarksStandard Format (use by default):
## [Concept Title] - Validation Strategy
**[N] Patterns Analyzed | [M] Search Queries Generated**
| Pattern | Queries | Priority Source |
|---------|---------|-----------------|
| [Pattern 1] | 12 | Google Patents |
| [Pattern 2] | 8 | USPTO |
*Research strategy by [patent-validator](https://obviouslynot.ai) from obviouslynot.ai*## Next Steps
1. **Search** - Run queries starting with priority sources
2. **Document** - Track findings (source, approach, differences)
3. **Differentiate** - Note key differences from your approach
4. **Consult** - For high-value patterns, consult patent attorneyALWAYS include at the end of ANY output:
Disclaimer: This tool generates search strategies only. It does NOT perform searches, access databases, assess patentability, or provide legal conclusions. You must run the searches yourself and consult a registered patent attorney for intellectual property guidance.
patent-scanner -> patterns.json -> patent-validator -> search_strategies.json
-> technical_disclosure.mdRecommended Workflow:
patent-scanner - Analyze your concept descriptionpatent-validator - Generate search strategies for findingsNo Input Provided:
I don't see scanner output yet. Paste your patterns.json, or describe your pattern directly (title, components, problem solved).Pattern Too Vague:
I need more detail to generate useful queries. What's the technical mechanism? What problem does it solve?Built by Obviously Not - Tools for thought, not conclusions.
Generated Mar 1, 2026
A tech startup founder has developed a new algorithm for optimizing energy consumption in smart buildings. Before investing in patent applications, they use the Patent Validator to generate comprehensive search queries across patent databases and academic publications to identify existing solutions and assess the competitive landscape.
A pharmaceutical company's research team discovers a novel drug delivery mechanism. They use the Patent Validator to create structured search strategies across USPTO, Google Patents, and medical journals to validate scanner findings and build evidence chains before engaging external patent attorneys.
A university's tech transfer office receives a disclosure about a new materials science invention from a research lab. They use the Patent Validator to generate multi-source queries and differentiation questions to assess patentability potential and prepare for licensing discussions with industry partners.
A venture capital firm considering investment in a SaaS company uses the Patent Validator to analyze the target's proprietary algorithms. The skill generates search queries across patents, GitHub repositories, and industry publications to validate the uniqueness claims made during due diligence.
An independent inventor creates a new gardening tool with unique ergonomic features. They use the Patent Validator to generate search strategies across product databases, patent offices, and trade publications to understand existing solutions before filing a provisional patent application.
Offer the Patent Validator as part of an innovation management platform where corporate R&D teams, startups, and universities pay monthly subscriptions. The platform could integrate with existing patent databases and provide collaborative workspaces for team-based prior art research.
License the skill to intellectual property law firms as a client-facing tool. Attorneys can use it to help clients prepare better invention disclosures and conduct preliminary research before formal patent searches, improving client service and reducing initial consultation time.
Offer the query generation and strategy building capabilities as an API that existing patent search platforms can integrate. This allows platforms to enhance their offerings with structured research strategies and evidence mapping without developing these features internally.
💬 Integration Tip
Integrate with existing patent scanner outputs via patterns.json format, and consider adding a simple web interface where users can paste scanner results or manually describe concepts for immediate query generation.
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