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Agent Skill · 效率

deepread-legal(深读法律)

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。

deepread-legal 是效率类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描已通过,按安装量在效率类的 21,003 个 Skill 里排第 14,380。

总安装 3,408周安装 142GitHub Stars 公开资料未说明下载 1,136核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

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。

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 deepread-legal

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

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。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install deepread-legal;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

deepread-legal 怎么安装?

在终端执行 openclaw skills install deepread-legal。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

deepread-legal 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

deepread-legal 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

deepread-legal 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

deepread-legal 用的人多吗?

公开数据是累计安装 3,408 次,近一周安装 142 次,下载 1,136 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

deepread-legal 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理效率类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
deepread-legal

深读法律 · 本页

3,408—接触敏感数据MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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

平台分布

OpenClaw

80.33%
按下载量换算913

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。目前只有一个公开来源,建议同时核对源仓库。

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