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deepread-legal深读法律

Agent Skill

deepread-legal 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。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。

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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:deepread-legal(深读法律)
来源仓库:https://github.com/uday390/deepread-legal
安装命令:
openclaw skills install deepread-legal
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。

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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 deepread-legal

简介

解析法律文书并提取核心要素的智能工具。deepread-legal 属于效率类 Skill,可作为该场景下的辅助能力补充。

  • 适用于合同审查、诉讼材料整理或合规文档管理。
  • 自动识别各方权利义务、签署日期与关键条款内容。
  • 处理敏感法律文件时建议人工复核确保准确性。
  • 安装后调用 API 即可获取标准化输出格式。

SKILL.md

name
deepread-legal
title
DeepRead Legal Documents
description
Extract structured data from contracts, legal agreements, court filings, and compliance documents. Pre-built schemas for parties, clauses, dates, obligations. PII redaction for privilege review. 97%+ accuracy. Free 2,000 pages/month.
metadata
{"openclaw":{"requires":{"env":["DEEPREAD_API_KEY"]},"primaryEnv":"DEEPREAD_API_KEY","homepage":"https://www.deepread.tech"}}

DeepRead Legal Document Processing

Extract structured data from contracts, legal agreements, NDAs, court filings, leases, and compliance documents. Then redact privileged or sensitive information before sharing with opposing counsel, auditors, or external parties.

This skill instructs the agent to POST documents to https://api.deepread.tech and poll for results. No system files are modified.

What You Get Back

Submit a contract and get structured JSON:

{
  "document_type": {"value": "Master Services Agreement", "hil_flag": false, "found_on_page": 1},
  "parties": {"value": [
    {"name": "Acme Corp", "role": "Service Provider", "address": "123 Tech Blvd, San Francisco, CA"},
    {"name": "GlobalCo Inc", "role": "Client", "address": "456 Market St, New York, NY"}
  ], "hil_flag": false, "found_on_page": 1},
  "effective_date": {"value": "2026-01-15", "hil_flag": false, "found_on_page": 1},
  "termination_date": {"value": "2027-01-14", "hil_flag": false, "found_on_page": 1},
  "governing_law": {"value": "State of California", "hil_flag": false, "found_on_page": 8},
  "contract_value": {"value": 250000.00, "hil_flag": true, "reason": "Multiple amounts found on different pages"},
  "payment_terms": {"value": "Net 45 from invoice date", "hil_flag": false, "found_on_page": 3},
  "key_clauses": {"value": [
    {"type": "Indemnification", "summary": "Provider indemnifies Client against third-party IP claims", "page": 5},
    {"type": "Limitation of Liability", "summary": "Capped at 12 months of fees paid", "page": 5},
    {"type": "Termination", "summary": "Either party may terminate with 30 days written notice", "page": 6},
    {"type": "Non-Compete", "summary": "12-month non-compete within same industry vertical", "page": 7}
  ], "hil_flag": false, "found_on_page": 5},
  "signatures": {"value": [
    {"name": "John Smith", "title": "CEO, Acme Corp", "date": "2026-01-10"},
    {"name": "Jane Doe", "title": "General Counsel, GlobalCo Inc", "date": "2026-01-12"}
  ], "hil_flag": false, "found_on_page": 8}
}

Fields with hil_flag: true need human review. Everything else is high-confidence.

Setup

Get Your API Key

open "https://www.deepread.tech/dashboard/?utm_source=clawhub"

Save it:

export DEEPREAD_API_KEY="sk_live_your_key_here"

Contract Schema

Pre-built schema for contracts and legal agreements:

{
  "type": "object",
  "properties": {
    "document_type": {"type": "string", "description": "Type of legal document (MSA, NDA, lease, employment agreement, etc.)"},
    "parties": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "name": {"type": "string", "description": "Full legal name of the party"},
          "role": {"type": "string", "description": "Role in the agreement (e.g., Licensor, Licensee, Landlord, Tenant)"},
          "address": {"type": "string", "description": "Address of the party"}
        }
      },
      "description": "All parties to the agreement"
    },
    "effective_date": {"type": "string", "description": "Date the agreement takes effect (YYYY-MM-DD)"},
    "termination_date": {"type": "string", "description": "End date or expiration of the agreement (YYYY-MM-DD)"},
    "governing_law": {"type": "string", "description": "Jurisdiction governing the agreement"},
    "contract_value": {"type": "number", "description": "Total contract value or consideration amount"},
    "payment_terms": {"type": "string", "description": "Payment schedule and terms"},
    "key_clauses": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "type": {"type": "string", "description": "Clause type (Indemnification, Limitation of Liability, Termination, Non-Compete, Confidentiality, IP Ownership, etc.)"},
          "summary": {"type": "string", "description": "Brief summary of the clause terms"},
          "page": {"type": "number", "description": "Page number where the clause appears"}
        }
      },
      "description": "Key clauses and their summaries"
    },
    "renewal_terms": {"type": "string", "description": "Auto-renewal terms if applicable"},
    "notice_period": {"type": "string", "description": "Required notice period for termination"},
    "signatures": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "name": {"type": "string", "description": "Signatory name"},
          "title": {"type": "string", "description": "Title and organization"},
          "date": {"type": "string", "description": "Date signed (YYYY-MM-DD)"}
        }
      },
      "description": "Signatories and execution dates"
    }
  }
}

Extract Data From Legal Documents

Python

import requests
import json
import time

API_KEY = "sk_live_YOUR_KEY"
BASE = "https://api.deepread.tech"
headers = {"X-API-Key": API_KEY}

schema = json.dumps({
    "type": "object",
    "properties": {
        "document_type": {"type": "string", "description": "Type of legal document"},
        "parties": {
            "type": "array",
            "items": {"type": "object", "properties": {
                "name": {"type": "string", "description": "Full legal name"},
                "role": {"type": "string", "description": "Role in agreement"}
            }},
            "description": "All parties"
        },
        "effective_date": {"type": "string", "description": "Effective date (YYYY-MM-DD)"},
        "termination_date": {"type": "string", "description": "End date (YYYY-MM-DD)"},
        "governing_law": {"type": "string", "description": "Governing jurisdiction"},
        "contract_value": {"type": "number", "description": "Total value"},
        "key_clauses": {
            "type": "array",
            "items": {"type": "object", "properties": {
                "type": {"type": "string", "description": "Clause type"},
                "summary": {"type": "string", "description": "Summary of terms"},
                "page": {"type": "number"}
            }},
            "description": "Key clauses"
        },
        "signatures": {
            "type": "array",
            "items": {"type": "object", "properties": {
                "name": {"type": "string"},
                "title": {"type": "string"},
                "date": {"type": "string"}
            }},
            "description": "Signatories"
        }
    }
})

# Submit contract
with open("contract.pdf", "rb") as f:
    job = requests.post(
        f"{BASE}/v1/process",
        headers=headers,
        files={"file": f},
        data={"schema": schema},
    ).json()

job_id = job["id"]
print(f"Processing: {job_id}")

# Poll for results
delay = 5
while True:
    time.sleep(delay)
    result = requests.get(f"{BASE}/v1/jobs/{job_id}", headers=headers).json()

    if result["status"] == "completed":
        data = result["result"]["data"]
        print(json.dumps(data, indent=2))

        # Flag fields needing review
        for field, value in data.items():
            if isinstance(value, dict) and value.get("hil_flag"):
                print(f"\
  REVIEW: {field} — {value.get('reason')}")
        break
    elif result["status"] == "failed":
        print(f"Failed: {result.get('error')}")
        break

    delay = min(delay * 1.5, 15)

cURL

curl -s -X POST https://api.deepread.tech/v1/process \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@contract.pdf" \
  -F 'schema={"type":"object","properties":{"document_type":{"type":"string","description":"Type of legal document"},"parties":{"type":"array","items":{"type":"object","properties":{"name":{"type":"string"},"role":{"type":"string"}}},"description":"All parties"},"effective_date":{"type":"string","description":"Effective date"},"governing_law":{"type":"string","description":"Governing jurisdiction"},"contract_value":{"type":"number","description":"Total value"},"key_clauses":{"type":"array","items":{"type":"object","properties":{"type":{"type":"string"},"summary":{"type":"string"}}},"description":"Key clauses"}}}'

Privilege Review: Redact Before Sharing

Redact privileged or sensitive information before sharing with opposing counsel, auditors, or external parties:

# Step 1: Extract the data you need
with open("contract.pdf", "rb") as f:
    extract_job = requests.post(
        f"{BASE}/v1/process",
        headers=headers,
        files={"file": f},
        data={"schema": schema},
    ).json()

# Step 2: Redact PII from the original before sharing
with open("contract.pdf", "rb") as f:
    redact_job = requests.post(
        f"{BASE}/v1/pii/redact",
        headers=headers,
        files={"file": f},
    ).json()

# Poll for redaction
redact_id = redact_job["id"]
delay = 5
while True:
    time.sleep(delay)
    result = requests.get(f"{BASE}/v1/pii/{redact_id}", headers=headers).json()
    if result["status"] == "completed":
        report = result["report"]
        print(f"Redacted {report['total_redactions']} PII instances")
        for pii_type, info in report["pii_detected"].items():
            print(f"  {pii_type}: {info['count']} found")
        pdf = requests.get(result["redacted_file_url"]).content
        with open("contract_redacted.pdf", "wb") as f:
            f.write(pdf)
        print("Saved: contract_redacted.pdf")
        break
    elif result["status"] == "failed":
        print(f"Failed: {result.get('error')}")
        break
    delay = min(delay * 1.5, 15)

Use Cases

  • Contract Review — Extract parties, dates, key clauses, and obligations from contracts and MSAs
  • NDA Analysis — Pull confidentiality terms, duration, exclusions, and governing law
  • Lease Extraction — Extract tenant, landlord, rent, term, renewal options from commercial leases
  • Court Filings — Pull case numbers, parties, filing dates, and relief sought from legal filings
  • Legal Discovery — Bulk-process documents, extract metadata, and redact privileged information
  • Compliance Audit — Extract regulatory clauses, reporting obligations, and compliance deadlines
  • M&A Due Diligence — Process stacks of contracts to extract key terms, liabilities, and change-of-control clauses
  • Employment Agreements — Pull compensation, non-compete terms, equity vesting, and termination clauses

Tips for Legal Documents

  • Specify clause types — Listing expected clause types (Indemnification, Limitation of Liability, etc.) in the schema description improves extraction
  • Use page numbers — Adding "page number where the clause appears" helps locate extracted terms in the original
  • Create blueprints for recurring document types — If you process the same type of contract repeatedly (e.g., NDAs, MSAs), train a blueprint at deepread.tech/dashboard/optimizer for 20-30% accuracy improvement
  • Always redact before external sharing — Use PII redaction before sending documents to opposing counsel, third-party reviewers, or LLMs

BYOK — Zero Processing Costs

Connect your own OpenAI, Google, or OpenRouter key via the dashboard. All document processing routes through your provider — zero DeepRead LLM costs, page quota skipped.

Set it up: https://www.deepread.tech/dashboard/byok

Related DeepRead Skills

  • deepread-ocr — General OCR and structured extraction — clawhub install uday390/deepread-ocr
  • deepread-pii — Redact PII from any document — clawhub install uday390/deepread-pii
  • deepread-form-fill — Fill PDF forms with AI vision — clawhub install uday390/deepread-form-fill
  • deepread-invoice — Invoice and receipt processing — clawhub install uday390/deepread-invoice
  • deepread-medical — Medical records processing — clawhub install uday390/deepread-medical
  • deepread-agent-setup — OAuth device flow authentication — clawhub install uday390/deepread-agent-setup
  • deepread-byok — Bring Your Own Key setup — clawhub install uday390/deepread-byok

Support

  • Dashboard: https://www.deepread.tech/dashboard
  • Demo Repo: https://github.com/deepread-tech/deepread-demo
  • n8n Node: https://www.npmjs.com/package/n8n-nodes-deepread
  • Issues: https://github.com/deepread-tech/deep-read-service/issues
  • Email: hello@deepread.tech

Get started free: https://www.deepread.tech/dashboard/?utm_source=clawhub

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