Contract Risk Analyzer

Contract Risk Analyzer · 合同风险智能审查 — 上传合同PDF，AI自动提取关键条款并标注风险点，输出结构化风险报告（文本摘要 + 关键条款表格 + 🔴🟠🟡三级风险列表）。支持采购/销售/服务/劳动/租赁/保密协议6种合同类型。触发词：合同审查、合同风险、合同分析、合同检查、合同审核

Contract Risk Reviewer · 合同风险智能审查

Trigger Keywords / 触发词： 合同审查、合同风险、合同分析、合同检查、合同审核、contract review、contract risk

When to use / 何时使用：

• User uploads a contract PDF and wants AI-powered risk analysis
• User asks to review/audit/check a contract for risks
• User provides a contract and asks for a structured risk report
• User mentions "合同审查"、"合同风险"、"合同分析"

---

What this skill does

上传合同 PDF → AI 分析 → 输出结构化风险报告（文本摘要 + 关键条款表格 + 风险点列表）

---

Workflow

Step 1 — Receive Contract File

The user uploads a PDF file. Download it to /tmp/contracts/ using the appropriate tool:

• If the file comes as a Feishu message attachment → use feishu_im_bot_image or feishu_im_user_fetch_resource with type=file
• If the file is a local path → copy or note the path directly
• If the file is a URL → use web_crawl or fetch

Store the file in /tmp/contracts/<uuid>.pdf.

Step 2 — Extract Text from PDF

Try in order:

1. PyMuPDF (fitz) — best for text-based PDFs:

   python

   import fitz
   doc = fitz.open(pdf_path)
   text = "\n".join(page.get_text() for page in doc)
   

2. pdfplumber — good for tables:

   python

   import pdfplumber
   with pdfplumber.open(pdf_path) as pdf:
       text = "\n".join(page.extract_text() or "" for page in pdf.pages)
   

3. OCR (pytesseract) — for scanned/image PDFs:

   • Convert PDF pages to images with pdf2image or PyMuPDF render
   • Run pytesseract with language packs (chi_sim + eng)
   • Fallback to Chinese + English bilingual OCR

If text extraction fails completely or yields < 50 characters, inform the user that the PDF may be a scanned image requiring OCR, and offer to process with OCR.

Step 3 — Auto-Detect Contract Type

Use the AI model to classify the contract type from extracted text:

• 劳动合同 (Labor/Employment Contract)
• 采购合同 (Purchase/Procurement Contract)
• 销售合同 (Sales Contract)
• 租赁合同 (Lease/Rental Contract)
• 保密协议 (NDA/Confidentiality Agreement)
• 其他 (Other)

Also detect language: 中文 / English / Bilingual.

Step 4 — AI Risk Analysis

Build a structured prompt for the AI model. Use model parameter from user's session or default to minimax/MiniMax-M2.

Prompt Structure:

text

# Contract Risk Analysis

## Contract Type: [detected type]
## Language: [Chinese / English / Bilingual]

## Contract Text:
[extracted text, truncated to last 8000 characters if too long]

---

Please analyze this contract and return a structured JSON report:

{
  "summary": "200-word-or-less summary of the contract's core content",
  "contract_type": "detected contract type",
  "language": "detected language",
  "key_terms": {
    "parties": ["Party A", "Party B", ...],
    "contract_value": "amount if stated, otherwise 'Not specified'",
    "payment_terms": "payment conditions summary",
    "duration": "contract duration/term",
    "termination": "termination conditions",
    "breach_penalties": "breach of contract penalties",
    "dispute_resolution": "dispute resolution clause",
    "governing_law": "applicable law/jurisdiction"
  },
  "risk_report": [
    {
      "level": "HIGH",    // HIGH / MEDIUM / LOW
      "category": "payment/termination/liability/confidentiality/other",
      "title": "Risk title",
      "description": "Detailed risk description",
      "clause_reference": "Which clause/section this risk comes from",
      "recommendation": "What the user should do about this risk"
    }
  ],
  "overall_score": 1-10,   // Risk score: 1=very low risk, 10=very high risk
  "overall_assessment": "Brief overall risk assessment paragraph"
}

IMPORTANT:
- Be strict and thorough — do not minimize real risks
- Classify risks as HIGH only if they involve significant financial loss, legal liability, or irreversible consequences
- If no risks found, return empty risk_report array
- This is NOT legal advice — include a disclaimer in the response to the user

Step 5 — Format and Deliver Results

Render the results as a well-formatted markdown report:

text

## 📄 合同风险审查报告

**合同类型：** [类型]
**语言：** [语言]
**整体风险评分：** [X/10] — [低/中/高]

---

### 📋 文本摘要

[200字以内摘要]

---

### 🔑 关键条款

| 条款 | 内容 |
|------|------|
| 当事人 | ... |
| 合同金额 | ... |
| 付款条件 | ... |
| 合同期限 | ... |
| 违约责任 | ... |
| 解除条款 | ... |
| 争议解决 | ... |
| 适用法律 | ... |

---

### ⚠️ 风险点列表

#### 🔴 高风险 (X项)

1. **[风险标题]**
   - 条款来源：第X条
   - 风险描述：...
   - 建议措施：...

#### 🟠 中风险 (X项)

...

#### 🟡 低风险 (X项)

...

---

⚠️ **免责声明：** 本报告仅供参考，不构成法律建议。如有法律疑问，请咨询专业律师。

---

📊 **统计数据**
- 文本字数：X字
- 检测到风险：X项（高X / 中X / 低X）
- 合同语言：中文/英文
- 分析时间：YYYY-MM-DD HH:mm

Step 6 — Save & Export

• Save the full report as /tmp/contracts/<uuid>_report.md
• If user requests Excel export (STD plan or above), generate a simple CSV/Excel format
• Send the report to the user via the current channel (Feishu message or direct display)

---

Tiered Features

Feature	FREE	STD (¥9.9)	PRO (¥29)	MAX (¥69)
Monthly limit	3 contracts	30 contracts	200 contracts	Unlimited
Contract types	Other only	All 6 types	All 6 types	All 6 types
Summary + Risk list	✅	✅	✅	✅
Key terms table	❌	✅	✅	✅
Excel report export	❌	✅	✅	✅
Batch processing	❌	❌	✅	✅
Risk comparison	❌	❌	✅	✅
API priority	❌	❌	❌	✅

For FREE tier: skip the key terms table, only deliver summary + risk list.

---

Token Validation

Check the user's token prefix in their session context or configuration:

• Token starting with CONTRACT-MAX → full access
• CONTRACT-PRO → PRO features
• CONTRACT-STD → STD features
• CONTRACT-FREE or none → FREE tier

If monthly limit is exceeded, inform the user and suggest upgrading.

---

Error Handling

Error	Handling
PDF extraction yields < 50 chars	Offer OCR processing; if OCR also fails, report failure and suggest providing a text-based PDF
AI analysis fails	Return error message; suggest retrying
Unsupported file type	Inform user only PDF is supported
Token validation missing	Default to FREE tier

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File Requirements

• All uploaded PDFs stored in /tmp/contracts/ (auto-cleanup optional)
• Reports saved in same directory with _report.md suffix
• Do NOT store contract text long-term; clean up after report is delivered

---

Tech Stack

• PDF Text: PyMuPDF (fitz) + pdfplumber
• OCR: pytesseract + pdf2image (with chi_sim+eng language packs)
• AI Analysis: OpenAI-compatible API via openai Python package
• Report Export: csv module for Excel CSV format

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Skill Metadata

• Slug: contract-risk-reviewer
• Name: 合同风险智能审查 (Contract Risk Reviewer)
• Platform: ClawHub (clawhub.ai) + 腾讯Skillhub
• Entry: scripts/analyze_contract.py
• Dependencies: fitz, pdfplumber, pytesseract, pdf2image, openai

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