Agent skill

Patent Professional Agents

by LeoYeAI in LeoYeAI/openclaw-master-skills

📜 专利专业代理 - Patent Professional Agents 一个专业的多代理专利撰写与优化技能套件,覆盖专利申请全流程。

MITAuto-check passedLegal & Compliance

Install Patent Professional Agents

skills CLI
$ npx skills add LeoYeAI/openclaw-master-skills --skill patent-professional-agents -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install LeoYeAI/openclaw-master-skills patent-professional-agents --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/patent-professional-agents .claude/skills/patent-professional-agents && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
patent-professional-agents
GitHub stars
2.2k
Token cost
~5k tokens
SKILL.md length
1,291 words
Files
14
Skills in repo
1,235
Repo updated
First seen
Licence
MIT

At a glance

📜 专利专业代理 - Patent Professional Agents 一个专业的多代理专利撰写与优化技能套件,覆盖专利申请全流程。

  • Works in 6 steps: Parse 7 sections of patent Markdown → Extract Mermaid code blocks and render… → Use Pandoc to convert section content → …
  • Tasks that involve Intellectual property
  • SKILL.md covers License, Core Positioning, Dependencies and Agent List (9 Core Agents), plus 5 more sections
  • Runs Python scripts from its folder; calls pip

What it does

Patent Professional Agents is an agent skill from LeoYeAI/openclaw-master-skills. 📜 专利专业代理 - Patent Professional Agents 一个专业的多代理专利撰写与优化技能套件,覆盖专利申请全流程。 🎯 核心功能: • 场景一:用户想法 → 技术挖掘 → 检索分析 → 专利撰写 → 质量审核 • 场景二:用户初稿 → 问题分析 → 优化建议 → 强化权利要求 • 场景三:代理机构反馈 → 风险评估 → 优化/取消建议 🤖 9个专业代理: tech-miner (技术挖掘)、prior-art-researcher (现有技术检索)、inventiveness-evaluator (创造性评估)、patent-drafter (专利撰写)、claims-architect (权利要求架构)、patent-analyst (专利分析)、patent-auditor (专利审核)、patent-value-appraiser (价值评估)、patent-converter (文档转换) ✨ 特色: • 中英文双语支持 • 7章节标准专利模板 • 授权率预判 • 自动Word文档转换 • 持续学习能力 🔍 搜索关键词:专利, patent, 专利撰写, 专利优化, 现有技术检索…

Its SKILL.md is about 5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 22 other files (for example `_meta.json`, `agents/claims-architect/SOUL.md` and `agents/inventiveness-evaluator/SOUL.md`).

It sits in Legal & Compliance, covering Intellectual property. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.

When your agent uses it

  • Tasks that involve Intellectual property

Example prompts

  • “/patent-professional-agents”

Requirements

  • Python 3

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Parse 7 sections of patent Markdown
  2. Extract Mermaid code blocks and render to PNG
  3. Use Pandoc to convert section content
  4. Fill into Word template at corresponding positions
  5. Embed images into document
  6. Output to same directory as source file

What it can do on your machine

Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships script files (Python, from the files we listed), which the agent can run.

    Shell commands in SKILL.md call:

    • pip

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Patent Professional Agents loads about 5k tokens when it runs. Until then it costs about 162 tokens; SKILL.md has 1,291 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~162
When it runs · the whole SKILL.md, loaded when a task matches
~5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 1,291 words, ~4,998 tokens.

Download SKILL.mdSave it as .claude/skills/patent-professional-agents/SKILL.md (or your agent's skills folder). This skill also uses 13 other files; get the full folder from GitHub.
name
patent-professional-agents
description
📜 专利专业代理 - Patent Professional Agents 一个专业的多代理专利撰写与优化技能套件,覆盖专利申请全流程。 🎯 核心功能: • 场景一:用户想法 → 技术挖掘 → 检索分析 → 专利撰写 → 质量审核 • 场景二:用户初稿 → 问题分析 → 优化建议 → 强化权利要求 • 场景三:代理机构反馈 → 风险评估 → 优化/取消建议 🤖 9个专业代理: tech-miner (技术挖掘)、prior-art-researcher (现有技术检索)、inventiveness-evaluator (创造性评估)、patent-drafter (专利撰写)、claims-architect (权利要求架构)、patent-analyst (专利分析)、patent-auditor (专利审核)、patent-value-appraiser (价值评估)、patent-converter (文档转换) ✨ 特色: • 中英文双语支持 • 7章节标准专利模板 • 授权率预判 • 自动Word文档转换 • 持续学习能力 🔍 搜索关键词:专利, patent, 专利撰写, 专利优化, 现有技术检索, 知识产权, IP, 权利要求, 技术交底书, 创造性评估, 授权率, patent drafting, prior art search, claims, patent prosecution
version
1.0.1
dependencies.skills
tavily-search, aminer-open-academic
dependencies.python
requests>=2.28.0, python-docx>=0.8.11

Professional Patent Agents Suite

License

MIT License

Copyright (c) 2026 BigPiPiHua

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.


Core Positioning

ScenarioInputOutputGoal
Scenario 1User idea (vague description)Complete patent document + Search reportGrant rate + Inventiveness
Scenario 2User draft (existing document)Optimized patent documentGrant rate + Inventiveness
Scenario 3Agency feedback (search report/prior art)Optimization suggestions / Cancellation adviceDecision support

Boundary: Does not handle Office Action (OA) responses - leave that to professional patent agencies.


Dependencies

Required Skills
SkillPurposeInstall Command
tavily-searchAI-optimized searchclawhub install tavily-search
aminer-open-academicAcademic paper searchclawhub install aminer-open-academic
Python Dependencies
bash
pip install requests python-docx

Agent List (9 Core Agents)

AgentRoleCore CapabilityPriority
tech-minerTechnology Mining ExpertIdea analysis, innovation extraction, technical disclosure framework⭐⭐⭐⭐⭐
prior-art-researcherPrior Art Search ExpertKeyword strategy + Multi-source search + Analysis⭐⭐⭐⭐⭐
inventiveness-evaluatorInventiveness Evaluation ExpertInventiveness analysis, risk scoring, grant rate prediction⭐⭐⭐⭐⭐
patent-drafterPatent Drafting Expert7-section drafting, Mermaid diagrams, document conversion⭐⭐⭐⭐⭐
claims-architectClaims ArchitectClaims design, scope optimization⭐⭐⭐⭐
patent-analystPatent AnalystDraft analysis, issue identification, optimization suggestions⭐⭐⭐⭐
patent-auditorPatent Audit ExpertQuality review, grant rate prediction, revision suggestions⭐⭐⭐⭐⭐
patent-value-appraiserPatent Value Appraiser5-dimension value assessment, market value estimation⭐⭐⭐⭐
patent-converterDocument Conversion ExpertMarkdown→Word, Mermaid diagram embedding⭐⭐⭐⭐

Workflows

mermaid
flowchart TB
    subgraph S1[Phase 1: Tech Mining]
        M1[tech-miner<br/>Understand idea] ~~~ M2[Extract innovations] ~~~ M3[Disclosure framework]
    end
    
    subgraph S2[Phase 2: Search]
        R1[prior-art-researcher<br/>Keyword strategy] ~~~ R2[Multi-source search] ~~~ R3[Analyze results]
    end
    
    subgraph S3[Phase 3: Evaluation]
        E1[inventiveness-evaluator<br/>Inventiveness analysis] ~~~ E2[Risk scoring] ~~~ E3[Differentiation advice]
    end
    
    subgraph S4[Phase 4: Drafting]
        D1[patent-drafter<br/>Draft specification] ~~~ C1[claims-architect<br/>Design claims]
    end
    
    subgraph S5[Phase 5: Review]
        A1[patent-auditor<br/>Full review] ~~~ A2[Grant rate prediction]
    end
    
    S1 --> S2 --> S3 --> S4 --> S5

Trigger:

"Help me write a patent: [technical idea]"
"I have an idea and want to apply for a patent"

Output Files:

  • TECH_DISCLOSURE.md - Technical disclosure framework
  • KEYWORD_STRATEGY.md - Keyword strategy
  • PATENT_SEARCH_REPORT.md - Search report
  • INVENTIVENESS_REPORT.md - Inventiveness evaluation report
  • Patent-*.md - Complete patent document (7-section standard format)
  • PATENT_AUDIT_REPORT.md - Audit report (with grant rate prediction)
  • Patent-*.docx - Word document (auto-converted)

Scenario 2: User Draft → Optimization
mermaid
flowchart TB
    subgraph P1[Phase 1: Analysis]
        A1[patent-analyst<br/>Parse draft] ~~~ A2[Identify issues] ~~~ A3[Extract keywords]
    end
    
    subgraph P2[Phase 2: Search]
        R1[prior-art-researcher<br/>Targeted search] ~~~ R2[Analyze results]
    end
    
    subgraph P3[Phase 3: Evaluation]
        E1[inventiveness-evaluator<br/>Inventiveness risk] ~~~ E2[Enhancement suggestions]
    end
    
    subgraph P4[Phase 4: Optimization]
        D1[patent-drafter<br/>Optimize specification] ~~~ C1[claims-architect<br/>Strengthen claims]
    end
    
    subgraph P5[Phase 5: Review]
        Q1[patent-auditor<br/>Full review] ~~~ Q2[Grant rate prediction]
    end
    
    P1 --> P2 --> P3 --> P4 --> P5

Trigger:

"Help me optimize this patent: /path/to/patent.md"
"Review this patent and provide optimization suggestions"

Output Files:

  • PATENT_ANALYSIS_REPORT.md - Analysis report
  • PATENT_SEARCH_REPORT.md - Search report
  • INVENTIVENESS_REPORT.md - Inventiveness evaluation report
  • PATENT_OPTIMIZATION_SUGGESTIONS.md - Optimization suggestions
  • Patent-*.md - Optimized patent document
  • PATENT_AUDIT_REPORT.md - Audit report

Scenario 3: Agency Feedback → Evaluation

Use Case: User has submitted to a patent agency, received a search report or prior art, needs to evaluate whether to continue optimizing or cancel the application.

mermaid
flowchart TB
    subgraph F1[Phase 1: Read Feedback]
        R1[Read search report] ~~~ R2[Read prior art] ~~~ R3[Read original draft]
    end
    
    subgraph F2[Phase 2: Comparative Analysis]
        A1[inventiveness-evaluator<br/>Comparison] ~~~ A2[Identify conflicts] ~~~ A3[Assess differentiation space]
    end
    
    subgraph F3[Phase 3: Decision]
        D1{Inventiveness space?}
        D2[🟢 Sufficient<br/>Recommend optimization]
        D3[🟡 Limited<br/>User confirmation needed]
        D4[🔴 No space<br/>Recommend cancellation]
        D1 --> D2
        D1 --> D3
        D1 --> D4
    end
    
    subgraph F4[Phase 4: Optimization]
        O1[patent-drafter<br/>Targeted optimization] ~~~ O2[Strengthen differences] ~~~ O3[patent-auditor<br/>Final review]
    end
    
    F1 --> F2 --> F3
    D2 --> F4
    D3 -->|User confirms| F4
    D4 --> X[Output cancellation report]

Trigger:

"The agency gave me a search report, help me see if I can optimize: /path/to/report.pdf"
"Here's the prior art, help me evaluate if I need to modify the patent"
"The agency says there's risk, should I continue or cancel?"

Output Files:

  • AGENCY_FEEDBACK_ANALYSIS.md - Agency feedback analysis
  • DECISION_RECOMMENDATION.md - Decision recommendation (continue/cancel)
  • PATENT_OPTIMIZATION_SUGGESTIONS.md - Targeted optimization suggestions

Decision Criteria:

Inventiveness SpaceBasisRecommendation
🟢 SufficientCore features not disclosed, clear differentiation pointsContinue optimization, strengthen differences
🟡 LimitedSome features disclosed, need repositioningUser confirmation required
🔴 No spaceCore features already disclosed, cannot circumventRecommend cancellation or redesign

Agent Details

Tech Miner (Technology Mining Expert)

Identity: Dr. Li, 15 years of technology assessment and innovation mining experience

Trigger: When user provides vague idea

Output: Technical disclosure framework

Use tech-miner to analyze the technical idea:
[User description]

Prior Art Researcher (Prior Art Search Expert)

Identity: Dr. Chen, 15 years of patent search experience

Trigger: When search is needed

Output: Search report + analysis

Use prior-art-researcher to search:
Keywords: [keywords]
Technical field: [field]

Search Channels (Default):

PriorityChannelToolPurpose
1Tavilytavily-searchQuick search, technical overview
2AMineraminer-open-academicAcademic papers + patent database
3Google Patentsweb_fetchGlobal patent full text
4GitHubtavily site:Open source projects
5Tech blogstavily site:Technical articles

⚠️ Patent Database APIs Recommended:

Default channels may not be sufficient for accurate patent prior art search. For professional patent search, recommend users to connect patent database APIs:

DatabaseAPI TypeCoverageBest For
Google PatentsPublic API100+ officesGlobal search
USPTOPublic APIUS patentsUS details
EPO (Espacenet)Public APIEuropean patentsEP search
CNIPAPublic APIChinese patentsCN search
WIPOPublic APIPCT applicationsInternational
Lens.orgFree APIGlobal patentsAcademic research

ClawHub Skill Discovery:

bash
# Always check ClawHub for patent search skills
clawhub search patent
clawhub search "prior art"

Inventiveness Evaluator (Inventiveness Evaluation Expert)

Identity: Dr. Zhao, former examiner, 12 years of evaluation experience

Trigger: After search completion

Output: Inventiveness evaluation report (with risk score)

Use inventiveness-evaluator to evaluate inventiveness:
Patent document: /path/to/patent.md
Search report: PATENT_SEARCH_REPORT.md

Patent Drafter (Patent Drafting Expert)

Identity: Patricia, 12 years of drafting experience, 92% grant rate

Trigger: After inventiveness evaluation passes

Output: Complete patent document (7 sections)

Use patent-drafter to draft patent:
Patent title: [title]
Technical disclosure: TECH_DISCLOSURE.md
Search report: PATENT_SEARCH_REPORT.md
Inventiveness evaluation: INVENTIVENESS_REPORT.md

Claims Architect (Claims Architect)

Identity: Claude, 1000+ claims experience

Trigger: Parallel participation during drafting phase

Output: Claims document

Use claims-architect to design claims:
Patent document: /path/to/patent.md
Core inventive points: [points]

Patent Analyst (Patent Analyst)

Identity: Dr. Zhang, 12 years of patent analysis experience

Trigger: First step in optimization scenario

Output: Analysis report + optimization suggestions

Use patent-analyst to analyze patent:
Patent document: /path/to/patent.md

Show full SKILL.md (514 more words)Show less
Patent Auditor (Patent Audit Expert)

Identity: Judge Wu, former examiner, reviewed 3000+ applications

Trigger: After drafting/optimization completion

Output: Audit report (with grant rate prediction)

Use patent-auditor to audit patent:
Patent document: /path/to/patent.md

Patent Value Appraiser (Patent Value Appraiser)

Identity: Ms. Lin, 10 years of patent valuation experience, certified IP asset appraiser

Trigger: User needs to evaluate existing patent value (transfer, pledge, financing)

Output: Patent value assessment report (5-dimension radar chart + market value range)

Use patent-value-appraiser to evaluate patent value:
Patent title: [title]
Or patent number: [number]
Purpose: pledge financing / licensing negotiation / technology transfer / M&A transaction

5 Evaluation Dimensions:

DimensionWeightContent
Technical Value25%Innovation degree, technical complexity, substitution difficulty
Legal Value25%Claim breadth, stability, invalidation resistance
Market Value25%Application scenarios, market size, competitive alternatives
Economic Value15%Cost savings, revenue potential, licensing income
Strategic Value10%Supply chain position, barrier strength, negotiation leverage

Patent Converter (Document Conversion Expert)

Identity: Alex, document conversion expert, proficient in Markdown → Word conversion

Trigger: Auto-triggered after patent-auditor review passes

Output: Word document (.docx), with embedded Mermaid diagrams

Conversion Flow:

  1. Parse 7 sections of patent Markdown
  2. Extract Mermaid code blocks and render to PNG
  3. Use Pandoc to convert section content
  4. Fill into Word template at corresponding positions
  5. Embed images into document
  6. Output to same directory as source file

Dependencies:

ToolPurpose
PandocMarkdown → Word conversion
mmdc (mermaid-cli)Mermaid → PNG rendering
python-docxWord document operations

Standard Patent Template (7 Sections)

markdown
# [Patent Title]

## 1. Related Prior Art and Their Defects or Deficiencies
### 1.1 Description of Prior Art
### 1.2 Defects or Deficiencies of Prior Art

## 2. Technical Improvements to Overcome the Above Defects

## 3. Alternative Solutions for Technical Improvements

## 4. Detailed Embodiments of the Technical Solution
### 4.1 System Architecture
### 4.2 Signal Logic Relationships
### 4.3 Implemented Functions
### 4.4 Specific Implementation Steps
### 4.5 Embodiment 1
(Describe included components/modules and their connections, signal logic; implemented functions and specific implementation steps)
## 5. Advantages of This Proposal Over Prior Art
(Achieved technical effects)
## 6. Related Drawings
(Structure diagrams with labeled component/module names; flowcharts with clear steps and process directions)
## 7. Claims
(Optional)

Language Adaptation

The agents automatically detect and use the user's language for output.

User Input LanguageOutput LanguageTemplate Format
EnglishEnglish7-Section Standard (English)
中文中文7章节标准模板(中文)
Other languagesUser's language7-Section Standard (translated)
Chinese 7-Section Template (中文七章节模板)
markdown
# [专利名称]

## 一、相关的现有技术及现有技术的缺陷或不足
### 1.1 现有技术描述
### 1.2 现有技术的缺陷或不足

## 二、为克服上述缺陷本提案的技术改进点

## 三、技术改进点的其他替代方案

## 四、详细的技术方案具体实施例
### 4.1 系统架构
### 4.2 信号逻辑关系
### 4.3 实现功能
### 4.4 具体实现步骤
### 4.5 实施例一

## 五、本提案相对现有技术的优点

## 六、相关附图

## 七、权利要求书
Key Rules for All Languages
  1. 7-Section Structure — Must follow the standard template regardless of language
  2. No Executable Code — Use pseudocode or flowcharts instead
  3. Quantified Technical Effects — Always quantify improvements (e.g., "30% efficiency increase")
  4. Comparison Table — Include comparison with prior art
  5. Mermaid Diagrams — Use flowcharts and architecture diagrams

Output Files Summary

Scenario 1: User Idea → Drafting
FileContentPhase
TECH_DISCLOSURE.mdTechnical disclosure frameworkTech mining
KEYWORD_STRATEGY.mdKeyword strategySearch
PATENT_SEARCH_REPORT.mdSearch reportSearch
INVENTIVENESS_REPORT.mdInventiveness evaluation reportEvaluation
Patent-*.mdComplete patent documentDrafting
PATENT_AUDIT_REPORT.mdAudit report (with grant rate)Review
Scenario 2: User Draft → Optimization
FileContentPhase
PATENT_ANALYSIS_REPORT.mdAnalysis reportAnalysis
PATENT_SEARCH_REPORT.mdSearch reportSearch
INVENTIVENESS_REPORT.mdInventiveness evaluation reportEvaluation
PATENT_OPTIMIZATION_SUGGESTIONS.mdOptimization suggestionsOptimization
PATENT_AUDIT_REPORT.mdAudit report (with grant rate)Review
Scenario 3: Agency Feedback → Evaluation
FileContentPhase
AGENCY_FEEDBACK_ANALYSIS.mdFeedback analysisAnalysis
DECISION_RECOMMENDATION.mdDecision recommendationDecision
PATENT_OPTIMIZATION_SUGGESTIONS.mdOptimization suggestions (if chosen)Optimization
Patent Value Assessment
FileContent
PATENT_VALUE_REPORT.md5-dimension value assessment + market value range

Installation Location

skills/
└── professional-patent-agents/
    ├── SKILL.md
    ├── agents/
    │   ├── tech-miner/
    │   ├── prior-art-researcher/
    │   ├── inventiveness-evaluator/
    │   ├── patent-drafter/
    │   ├── claims-architect/
    │   ├── patent-analyst/
    │   ├── patent-auditor/
    │   ├── patent-value-appraiser/
    │   └── patent-converter/
    └── skills/
        └── continuous-learning/

Auto-Conversion Flow

Trigger Conditions

Auto-invoke patent-converter to convert Markdown to Word when:

ConditionRequirement
patent-auditor review resultPassed
Grant rate prediction≥ 60% (low/medium risk)
User confirmationHigh risk (< 60%) requires user confirmation
Conversion Flow
mermaid
flowchart TB
    A[patent-auditor<br/>Review complete] --> B{Grant rate ≥ 60%?}
    B -->|Yes| C[Auto-invoke<br/>patent-converter]
    B -->|No| D[Prompt user confirmation]
    D -->|Confirm convert| C
    D -->|Don't convert| E[Output Markdown only]
    C --> F[Output .docx file]
    F --> G[Notify user<br/>Ready for agency submission]
Output Location
Source directory/
├── Patent-1-xxx.md      # Source Markdown
├── Patent-1-xxx.docx    # Converted output (same directory)
├── Patent-2-xxx.md
├── Patent-2-xxx.docx
└── ...

Innovation Mining & Notifications

Work Record Source
memory/
├── 2026-03-16.md    # Daily work records
├── 2026-03-17.md
├── 2026-03-18.md
└── ...
Innovation Mining Rules
  1. Extract technical points from work records: Code commits, architecture designs, problem solutions
  2. Combine with industry trends: Search for latest technical developments
  3. Evaluate grant rate: Prior art search + Inventiveness evaluation
  4. Selection criteria: Grant rate ≥ 65%, Low/Medium risk level
Notification Format
📢 Innovation Mining Report

📊 X potential innovations discovered this week:

1. 【Highly Recommended】A method for XXX
   - Grant rate prediction: 70-80%
   - Risk level: Low
   - Innovation: XXX

2. 【Recommended】A system for XXX
   - Grant rate prediction: 65-75%
   - Risk level: Medium
   - Innovation: XXX

📁 Detailed documents: /patent/weekly/

💡 Suggestion: Prioritize applying for patent #1

Professional Patent Agents Suite v1.0 Author: BigPiPiHua Mail: 775262592@qq.com License: MIT Updated: 2026-03-19

© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 13 other files in skills/patent-professional-agents of LeoYeAI/openclaw-master-skills.

  • SKILL.md
  • _meta.json
  • agents/claims-architect/SOUL.md
  • agents/inventiveness-evaluator/SOUL.md
  • agents/patent-analyst/SOUL.md
  • agents/patent-auditor/SOUL.md
  • agents/patent-converter/SOUL.md
  • agents/patent-converter/convert_patents.py
  • agents/patent-drafter/SOUL.md
  • agents/patent-value-appraiser/SOUL.md
  • agents/prior-art-researcher/SOUL.md
  • agents/tech-miner
  • … and 2 more

Open the folder on GitHubat commit e5199b5

Compare with similar skills

Patent Professional Agents next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Patent Professional Agents compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Patent Professional Agents this skillLeoYeAI/openclaw-master-skills2.2k—~5kAutomated safety check: PassMIT
Paper to Chinese Patent DrafterYuan1z0825/nature-skills47k1 repos~1.1kAutomated safety check: PassApache-2.0
Paper To Cn Patentsnipp-zha/Paper-to-patent-Skill1071 repos~959Automated safety check: PassNone
Patent Examinegfodor/legal-skills393—~4.8kAutomated safety check: PassGPL-3.0
Patent Auditgfodor/legal-skills393—~2.9kAutomated safety check: PassGPL-3.0
Replica BrandJakeschincariol/replica-skill1.4k—~1.1kAutomated safety check: PassMIT

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  • Paper to Chinese Patent Drafter

    Yuan1z0825/nature-skills

    Drafts Chinese invention patent applications and technical disclosures from research papers or inventor materials, tying each claim feature to source evidence.

    47k GitHub starsUsed in 1 repo~1.1k tokens
    Legal & ComplianceAuto-check passed
  • Paper To Cn Patent

    snipp-zha/Paper-to-patent-Skill

    Convert scientific papers, theses, technical reports, source code, figures, or research manuscripts into evidence-grounded Chinese invention patent drafts.

    107 GitHub starsUsed in 1 repo~959 tokens
    Legal & ComplianceAuto-check passed
  • Patent Examine

    gfodor/legal-skills

    Iteratively examine and revise a draft U.S. An agent skill from gfodor/legal-skills.

    393 GitHub stars~4.8k tokensUpdated 1 mo ago
    Legal & ComplianceAuto-check passed
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    Audit a draft U.S. An agent skill from gfodor/legal-skills.

    393 GitHub stars~2.9k tokensUpdated 1 mo ago
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All 1,200 skills in this repo
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Questions about Patent Professional Agents

What does Patent Professional Agents do?

📜 专利专业代理 - Patent Professional Agents 一个专业的多代理专利撰写与优化技能套件,覆盖专利申请全流程。. Patent Professional Agents is an agent skill from LeoYeAI/openclaw-master-skills.

When should I use Patent Professional Agents?

Patent Professional Agents fits situations like: tasks that involve Intellectual property.

How do I install Patent Professional Agents in Claude Code?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill patent-professional-agents -a claude-code`. Or copy the skill folder (skills/patent-professional-agents in LeoYeAI/openclaw-master-skills) into .claude/skills/patent-professional-agents in your project. Claude Code loads it when a task matches its description.

How do I install Patent Professional Agents in Codex?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill patent-professional-agents -a codex`. Or copy the skill folder (skills/patent-professional-agents in LeoYeAI/openclaw-master-skills) into .agents/skills/patent-professional-agents in your project. Codex loads it when a task matches its description.

Can I use Patent Professional Agents in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeoYeAI/openclaw-master-skills --skill patent-professional-agents -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/patent-professional-agents, .gemini/skills/patent-professional-agents, .github/skills/patent-professional-agents and .opencode/skills/patent-professional-agents in your project.

What does Patent Professional Agents need to run?

Going by SKILL.md and its folder, Patent Professional Agents needs Python for the scripts in its folder and the command-line tools its instructions call (pip). Our summary lists: Python 3.

Does Patent Professional Agents access the network?

SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Patent Professional Agents safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Patent Professional Agents use?

Patent Professional Agents is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Patent Professional Agents use?

About 5k tokens (SKILL.md is roughly 20k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Patent Professional Agents?

Skills that share tags, products or a category with Patent Professional Agents: Paper to Chinese Patent Drafter (Yuan1z0825/nature-skills, 47k stars), Paper To Cn Patent (snipp-zha/Paper-to-patent-Skill, 107 stars), Patent Examine (gfodor/legal-skills, 393 stars) and Patent Audit (gfodor/legal-skills, 393 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Patent Professional Agents?

LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,161 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.

Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.