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patent-validator专利验证器

Agent Skill

patent-validator 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

75,605

周安装

3,119

GitHub Stars

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下载量

24,702
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:patent-validator(专利验证器)
来源仓库:https://github.com/leegitw/patent-validator
安装命令:
openclaw skills install patent-validator
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install patent-validator

简介

分析技术构想并生成精准专利检索查询语句,提高查全率。

  • 适用于研发初期快速判断技术是否落入现有保护范围。
  • 避免无效检索,节省时间与数据库资源消耗。patent-validator 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 安装命令:openclaw skills install patent-validator。
  • 检索结果仅供参考,不能作为是否侵权的最终依据。

SKILL.md

name
Patent Validator
description
Turn your concept analysis into search queries — research the landscape before consulting an attorney. NOT legal advice.
homepage
https://github.com/Obviously-Not/patent-skills/tree/main/patent-validator
user-invocable
true
emoji
🔎
tags

Patent Validator

Agent Identity

Role: 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

Validator Role

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.

When to Use

Activate this skill when the user asks to:

  • "Help me search for similar implementations"
  • "Generate search queries for my concept"
  • "What should I search for?"
  • "Validate my patent-scanner findings"
  • "Create a research strategy"

Important Limitations

  • Generates search queries only - does NOT perform searches
  • Cannot assess uniqueness or patentability
  • Cannot replace professional patent search
  • Provides tools for research, not conclusions

Process Flow

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."

Input Options

Option 1: From patent-scanner Output

I have patent-scanner results to validate:
[paste patterns.json or summary]

Option 2: Manual Description

Validate this concept:
- Pattern: [title]
- Components: [what's combined]
- Problem solved: [description]
- Claimed benefit: [what makes it different]

Search Strategy Generation

1. Multi-Source Query Generation

For each pattern, generate queries for:

SourceQuery TypeBest For
Google PatentsBoolean combinationsPatent landscape
USPTOCPC codes + keywordsUS patents
Google ScholarAcademic phrasingResearch papers
Industry PublicationsTrade terminologyMarket solutions

Query Variations per Pattern:

  • Exact combination: "[A]" AND "[B]" AND "[C]"
  • Functional: "[A]" FOR "[purpose]"
  • Synonyms: "[A-synonym]" WITH "[B-synonym]"
  • Broader category: "[A-category]" AND "[B-category]"
  • Narrower: "[A]" AND "[B]" AND "[specific detail]"

2. Search Priority Guidance

Prioritize sources based on pattern type:

Pattern TypePriority Order
Process/MethodPatents -> Publications -> Products
HardwarePatents -> Products -> Publications
Software-adjacentPatents -> GitHub -> Publications
Research/AcademicPublications -> Patents -> Products

3. Evidence Mapping (JB-4)

For each scanner pattern, build a provenance chain linking claim angles to evidence:

Evidence TypeWhat to DocumentWhy It Matters
Prototypesdemo-v1Proves concept works
TimelineFirst conceived 2026-01Establishes priority
DocumentationDesign specShows intentional innovation
ValidationUser testing resultsQuantifies benefit

Provenance chain: Each claim angle (from scanner) traces to specific evidence. This creates a clear trail from abstract claim to concrete validation.

4. Differentiation Analysis Framework

Questions to guide analysis of search results:

Technical Differentiation:

  • What's different in your approach vs. found results?
  • What technical advantages does yours offer?
  • What performance improvements exist?

Problem-Solution Fit:

  • What problems does yours solve that others don't?
  • Does your approach address limitations of existing solutions?
  • Is the problem framing itself different?

Synergy Assessment:

  • Does the combination produce unexpected benefits?
  • Is the result greater than sum of parts (1+1=3)?
  • What barriers existed before this approach?

Output Schema

{
  "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"
  ]
}

Output Format

Search Strategy Report

# 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 benchmarks

Share Card Format

Standard 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 (Required in All Outputs)

## 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 attorney

Terminology Rules (MANDATORY)

Never Use

  • "patentable"
  • "novel" (legal sense)
  • "non-obvious"
  • "prior art"
  • "claims"
  • "already patented"

Always Use Instead

  • "distinctive"
  • "unique"
  • "sophisticated"
  • "existing implementations"
  • "already implemented"

Required Disclaimer

ALWAYS 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.

Workflow Integration

patent-scanner -> patterns.json -> patent-validator -> search_strategies.json
                                                    -> technical_disclosure.md

Recommended Workflow:

  1. Start: patent-scanner - Analyze your concept description
  2. Then: patent-validator - Generate search strategies for findings
  3. User: Run searches, document findings
  4. Final: Consult patent attorney with documented findings

Error Handling

No 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?

Related Skills

  • patent-scanner: Analyze concept descriptions (run this first)
  • code-patent-scanner: Analyze source code
  • code-patent-validator: Validate code pattern distinctiveness

*Built by Obviously Not - Tools for thought, not conclusions.*

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

96.11%
按下载量换算23,741

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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