Professional Patent Agents

👤 bigpipihua 📦 v1.0.2 ⭐ 4.5 ⬇️ 1.4K 下载
💼 行业专业 免费 🔑 需 API Key

📖 技能介绍


name: professional-patent-agents version: 1.0.2 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

dependencies: skills: - tavily-search - aminer-open-academic python: - requests>=2.28.0 - python-docx>=0.8.11 system: - pandoc>=2.0 (Markdown转Word) - node>=18 (mermaid-cli依赖) - mmdc/mermaid-cli (Mermaid图表渲染) - chromium (Puppeteer浏览器,可选)


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

Scenario Input Output Goal
Scenario 1 User idea (vague description) Complete patent document + Search report Grant rate + Inventiveness
Scenario 2 User draft (existing document) Optimized patent document Grant rate + Inventiveness
Scenario 3 Agency feedback (search report/prior art) Optimization suggestions / Cancellation advice Decision support

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


Dependencies

Required Skills

Skill Purpose Install Command
tavily-search AI-optimized search clawhub install tavily-search
aminer-open-academic Academic paper search clawhub install aminer-open-academic

Python Dependencies

pip install requests python-docx

Agent List (9 Core Agents)

Agent Role Core Capability Priority
tech-miner Technology Mining Expert Idea analysis, innovation extraction, technical disclosure framework ⭐⭐⭐⭐⭐
prior-art-researcher Prior Art Search Expert Keyword strategy + Multi-source search + Analysis ⭐⭐⭐⭐⭐
inventiveness-evaluator Inventiveness Evaluation Expert Inventiveness analysis, risk scoring, grant rate prediction ⭐⭐⭐⭐⭐
patent-drafter Patent Drafting Expert 7-section drafting, Mermaid diagrams, document conversion ⭐⭐⭐⭐⭐
claims-architect Claims Architect Claims design, scope optimization ⭐⭐⭐⭐
patent-analyst Patent Analyst Draft analysis, issue identification, optimization suggestions ⭐⭐⭐⭐
patent-auditor Patent Audit Expert Quality review, grant rate prediction, revision suggestions ⭐⭐⭐⭐⭐
patent-value-appraiser Patent Value Appraiser 5-dimension value assessment, market value estimation ⭐⭐⭐⭐
patent-converter Document Conversion Expert Markdown→Word, Mermaid diagram embedding ⭐⭐⭐⭐

Workflows

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

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

发现更多技能插件,请访问7w4.net。

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.

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 Space Basis Recommendation
🟢 Sufficient Core features not disclosed, clear differentiation points Continue optimization, strengthen differences
🟡 Limited Some features disclosed, need repositioning User confirmation required
🔴 No space Core features already disclosed, cannot circumvent Recommend 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): | Priority | Channel | Tool | Purpose | |----------|---------|------|---------| | 1 | Tavily | tavily-search | Quick search, technical overview | | 2 | AMiner | aminer-open-academic | Academic papers + patent database | | 3 | Google Patents | web_fetch | Global patent full text | | 4 | GitHub | tavily site: | Open source projects | | 5 | Tech blogs | tavily 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:

Database API Type Coverage Best For
Google Patents Public API 100+ offices Global search
USPTO Public API US patents US details
EPO (Espacenet) Public API European patents EP search
CNIPA Public API Chinese patents CN search
WIPO Public API PCT applications International
Lens.org Free API Global patents Academic research

ClawHub Skill Discovery:

# 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

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: | Dimension | Weight | Content | |-----------|--------|---------| | Technical Value | 25% | Innovation degree, technical complexity, substitution difficulty | | Legal Value | 25% | Claim breadth, stability, invalidation resistance | | Market Value | 25% | Application scenarios, market size, competitive alternatives | | Economic Value | 15% | Cost savings, revenue potential, licensing income | | Strategic Value | 10% | 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: | Tool | Purpose | |------|---------| | Pandoc | Markdown → Word conversion | | mmdc (mermaid-cli) | Mermaid → PNG rendering | | python-docx | Word document operations |


Standard Patent Template (7 Sections)

# [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 Language Output Language Template Format
English English 7-Section Standard (English)
中文 中文 7章节标准模板(中文)
Other languages User's language 7-Section Standard (translated)

Chinese 7-Section Template (中文七章节模板)

# [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

File Content Phase
TECH_DISCLOSURE.md Technical disclosure framework Tech mining
KEYWORD_STRATEGY.md Keyword strategy Search
PATENT_SEARCH_REPORT.md Search report Search
INVENTIVENESS_REPORT.md Inventiveness evaluation report Evaluation
Patent-*.md Complete patent document Drafting
PATENT_AUDIT_REPORT.md Audit report (with grant rate) Review

Scenario 2: User Draft → Optimization

File Content Phase
PATENT_ANALYSIS_REPORT.md Analysis report Analysis
PATENT_SEARCH_REPORT.md Search report Search
INVENTIVENESS_REPORT.md Inventiveness evaluation report Evaluation
PATENT_OPTIMIZATION_SUGGESTIONS.md Optimization suggestions Optimization
PATENT_AUDIT_REPORT.md Audit report (with grant rate) Review

Scenario 3: Agency Feedback → Evaluation

File Content Phase
AGENCY_FEEDBACK_ANALYSIS.md Feedback analysis Analysis
DECISION_RECOMMENDATION.md Decision recommendation Decision
PATENT_OPTIMIZATION_SUGGESTIONS.md Optimization suggestions (if chosen) Optimization

Patent Value Assessment

File Content
PATENT_VALUE_REPORT.md 5-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:

Condition Requirement
patent-auditor review result Passed
Grant rate prediction ≥ 60% (low/medium risk)
User confirmation High risk (< 60%) requires user confirmation

Conversion Flow

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

⚠️ Security & Installation Guide

System Dependencies

# 1. Install Pandoc (Markdown to Word conversion)
apt install pandoc

# 2. Install Node.js and mermaid-cli (Mermaid diagram rendering)
curl -fsSL https://deb.nodesource.com/setup_18.x | bash -
apt install nodejs
npm install -g @mermaid-js/mermaid-cli

# 3. Install Chromium (optional, for Playwright/Puppeteer)
playwright install chromium

Security Considerations

Risk Description Recommendation
Puppeteer --no-sandbox Required when running as root, reduces browser sandboxing Run in Docker container or non-root user
Network requests Downloads PDFs and accesses third-party sites Run in isolated environment
Default paths Converter uses /root/workspace/patent/new as default Verify working directory before running
# Option 1: Non-root user (recommended)
python convert_patents.py /path/to/patents

# Option 2: Docker container (isolated environment)
docker run -v /path/to/patents:/data your-image python convert_patents.py /data

Credential Management

This skill depends on other skills that may require API keys or cookies:

Skill Credentials Needed
tavily-search Tavily API key
aminer-open-academic AMiner API key (optional)

Configure credentials securely before use.


Professional Patent Agents Suite v1.0.2 Author: BigPiPiHua Mail: 775262592@qq.com License: MIT Updated: 2026-03-31

🤖 AI 评测

质量较高,是一个非常专业的专利撰写辅助工具。优点在于多代理协作流畅、流程覆盖全面、双语支持友好、持续学习能力强,能有效提升专利申请质量并预测授权可能性。不足是依赖较多外部工具可能导致安装复杂,部分代理描述完整度待验证。适合需要频繁撰写或优化专利的用户使用。

📊 多维度评分

适应性4.7
规范性4.5
有效性4.7
可靠性4.2
可信度4.7

📁 包含文件 (13 个)

📄 SKILL.md 22.2 KB
📄 _meta.json 145 B
📄 agents/claims-architect/SOUL.md 6.4 KB
📄 agents/inventiveness-evaluator/SOUL.md 7.6 KB
📄 agents/patent-analyst/SOUL.md 8.4 KB
📄 agents/patent-auditor/SOUL.md 8.6 KB
📄 agents/patent-converter/SOUL.md 6.1 KB
📄 agents/patent-converter/convert_patents.py 15.9 KB
📄 agents/patent-drafter/SOUL.md 7.8 KB
📄 agents/patent-value-appraiser/SOUL.md 8.6 KB
📄 agents/prior-art-researcher/SOUL.md 9.2 KB
📄 agents/tech-miner/SOUL.md 4.9 KB
📄 skills/continuous-learning/SKILL.md 7 KB