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code-patent-validator代码专利验证器

Agent Skill

code-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

71,375

周安装

3,004

GitHub Stars

14

下载量

24,993
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:code-patent-validator(代码专利验证器)
来源仓库:https://github.com/leegitw/code-patent-validator
安装命令:
openclaw skills install code-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 code-patent-validator

简介

将代码扫描结果转化为专利检索查询,辅助技术调研。

  • 适用于需要分析代码实现并查找相关专利或现有技术的场景。
  • 通过关键词生成和筛选提升检索效率,支持初步法律风险排查。
  • 安装前请确认权限范围、维护状态及是否触发联网或文件操作。
  • code-patent-validator 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
Code Patent Validator
description
Turn your code scan findings into search queries — research existing implementations before consulting an attorney. NOT legal advice.
homepage
https://github.com/Obviously-Not/patent-skills/tree/main/code-patent-validator
user-invocable
true
emoji
tags

Code 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 findings"
  • "Validate my code-patent-scanner results"
  • "Create a research strategy for these patterns"

Important Limitations

  • This skill generates search queries only - it 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 findings from code-patent-scanner
   - patterns.json with scored distinctive patterns
   - 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 JSON: "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."
- No scanner output: "I don't see scanner output yet. Paste your patterns.json, or describe your pattern directly."

Search Strategy Generation

1. Multi-Source Query Generation

For each pattern, generate queries for:

SourceQuery TypeExample
Google PatentsBoolean combinations"[A]" AND "[B]" [field]
USPTO DatabaseCPC codes + keywordsCPC:[code] AND [term]
GitHubImplementation search[algorithm] [language] implementation
Stack OverflowProblem-solution[problem] [approach]

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

Suggest which sources to search first based on pattern type:

Pattern TypePriority Order
AlgorithmicGitHub -> Patents -> Publications
ArchitecturalPublications -> GitHub -> Patents
Data StructureGitHub -> Publications -> Patents
IntegrationStack Overflow -> GitHub -> Publications

3. Evidence Mapping (JB-4)

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

Evidence TypeWhat to DocumentWhy It Matters
Source linesfile.go:45-120Proves implementation exists
Commit historyabc123 (2026-01-15)Establishes timeline
Design docsRFC-042Shows intentional innovation
Benchmarks40% fasterQuantifies benefit

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

4. Differentiation Questions

Questions to guide user's 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": 7
  },
  "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"],
        "uspto": ["query1"],
        "github": ["query1"],
        "stackoverflow": ["query1"]
      },
      "search_priority": [
        {"source": "google_patents", "reason": "Technical implementation focus"},
        {"source": "github", "reason": "Open source implementations"}
      ],
      "analysis_questions": [
        "How does your approach differ from [X]?",
        "What technical barrier did you overcome?"
      ],
      "evidence_map": {
        "claim_angle_1": {
          "source_files": ["path/to/file.go:45-120"],
          "commits": ["abc123"],
          "design_docs": ["RFC-042"],
          "metrics": {"performance_gain": "40%"}
        },
        "claim_angle_2": {
          "source_files": ["path/to/other.go:10-50"],
          "commits": ["def456"],
          "design_docs": [],
          "metrics": {}
        }
      }
    }
  ],
  "next_steps": [
    "Run generated searches yourself",
    "Document findings systematically",
    "Note differences from existing implementations",
    "Consult patent attorney for legal assessment"
  ]
}

Share Card Format

Standard Format (use by default):

## [Repository Name] - 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 [code-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 systematically
3. **Differentiate** - Note differences from existing implementations
4. **Consult** - For high-value patterns, consult patent attorney

**Evidence checklist**: specs, git commits, benchmarks, timeline, design decisions

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

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

Recommended Workflow:

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

Related Skills

  • code-patent-scanner: Analyze source code (run this first)
  • patent-scanner: Analyze concept descriptions (no code)
  • patent-validator: Validate concept 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

80.13%
按下载量换算20,027

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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