Human-Rent Skill
Human-as-a-Service platform for AI Agents
Enable OpenClaw agents to dispatch real human workers for physical world tasks that AI cannot perform: take photos, verify addresses, inspect equipment, make phone calls, and more.
Core Concept
Transform AI agents from "digital-only" to "hybrid intelligence" by giving them the ability to interact with the physical world through verified human workers.
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Installation
The skill is self-contained and ready to use after installation:
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Configuration
Set up your ZhenRent API credentials:
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Get your credentials at: https://www.zhenrent.com/api/keys
Test Installation
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When to Use This Skill
Consider using this skill when the user's request involves:
- - Physical verification: Check if an address exists, verify a business is open
- Photo evidence: Take a photo of something, get visual proof
- Real-world inspection: Inspect equipment, check product availability
- Human interaction: Make phone calls, ask questions in person
- Trust verification: Confirm something exists in the physical world
Example Scenarios:
- - "I need someone to verify this address in San Francisco"
- "Take a photo of the building at 123 Main Street"
- "Check if this store has the product in stock"
- "Call this number and confirm the appointment"
- "Inspect this equipment and report its condition"
Do NOT use when:
- - Task can be done with digital APIs (use web search, image API, etc.)
- No physical presence required
- Task is illegal or dangerous
Important: User Confirmation Required
This skill ALWAYS requires explicit user confirmation before dispatching human workers because:
- 1. Real humans will be dispatched to physical locations
- The user will be charged for the service ($15-100 per task)
- Physical world actions have real consequences
The CLI will automatically prompt for confirmation. For non-interactive use, set:
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Usage
Dispatch Human Task
When a user requests physical-world action, execute:
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Options:
- -
--location=<lat,lng> - Location coordinates (e.g., "37.7749,-122.4194") - INLINECODE1 - Budget in dollars (e.g., "$20" or "$15-25")
- INLINECODE2 - Priority: low, normal, high, urgent
- INLINECODE3 - Task timeout in minutes (default: 30)
- INLINECODE4 - Task type (auto-detected if not specified)
Check Task Status
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List Available Humans
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Task Types
Layer 1: Instant Human (Currently Available)
| Type | Description | Latency | Cost |
|---|
| INLINECODE5 | Take a photo of something | 5-15 min | $10-20 |
| INLINECODE6 |
Verify physical address exists | 10-20 min | $15-25 |
|
document_scan | Scan a physical document | 10-20 min | $15-25 |
|
visual_inspection | Detailed visual inspection | 15-30 min | $20-40 |
|
voice_verification | Make a phone call and verify | 5-10 min | $10-20 |
|
purchase_verification | Check product availability | 15-30 min | $20-40 |
Future Layers (Planned)
Layer 2: Expert on Call
- - Legal document review
- Medical image analysis
- Code audit
- Professional consultation
Layer 3: Embodied Agent
- - Attend meetings
- Equipment installation
- Long-term physical monitoring
Technical Architecture
Async Function Calling Pattern
Human tasks are asynchronous and take minutes to hours to complete. The workflow is:
- 1. Agent dispatches task (with user confirmation)
- Task is assigned to a human worker
- Agent receives task ID and continues other work
- Agent periodically checks task status
- When completed, agent processes results
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Authentication
All API requests use HMAC-SHA256 authentication:
- 1. Generate timestamp
- Create message: INLINECODE11
- Sign with HMAC-SHA256 using API secret
- Include signature in request headers
The CLI handles authentication automatically when you set the environment variables.
Strategic Value
1. Capability Differentiation
Problem: All AI agents are limited to digital information
Solution: OpenClaw can verify physical reality
Example Use Cases:
- - Due diligence: Investor agent verifies company office exists before investment
- E-commerce: Purchasing agent inspects warehouse before bulk order
- Security: Safety agent verifies suspicious package before opening
2. Hybrid Intelligence Workflows
Enable "Human-in-the-Loop" automation:
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This makes OpenClaw agents auditable and trustworthy for regulated industries (finance, healthcare, legal).
3. New Revenue Model
- - Per-task fee: $15-50/task
- Platform fee: 20% commission
- Subscription: $99/month for unlimited tasks
Cost Estimation
| Task Type | Human Time | Human Cost | Platform Fee (20%) | Total Cost |
|---|
| Quick photo | 10 min | $10 | $2 | $12 |
| Address verify |
20 min | $20 | $4 | $24 |
| Detailed inspect | 30 min | $30 | $6 | $36 |
| Expert consult | 60 min | $100 | $20 | $120 |
Configuration Options
Task Requirements
You can specify requirements when dispatching tasks:
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For advanced requirements, use the API directly with:
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Usage Examples
Example 1: Real Estate Investment
Scenario: AI agent analyzing potential property investment
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Example 2: Vendor Verification
Scenario: Procurement agent vetting new supplier
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Example 3: Address Verification
Scenario: Verifying customer shipping address
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Troubleshooting
Issue 1: No Humans Available
Error: "No suitable humans found for this task"
Solutions:
- - Expand search radius (use
--radius option) - Increase budget to attract workers
- Try different time of day
- Check if location is accessible
Issue 2: Task Timeout
Error: "Task timed out"
Solutions:
- - Increase timeout (use
--timeout option) - Check if location is accessible
- Verify task is clear and reasonable
- Increase budget for complex tasks
Issue 3: Authentication Error
Error: "Missing credentials" or "Authentication failed"
Solutions:
- - Verify environment variables are set correctly
- Check API key is valid at https://www.zhenrent.com/api/keys
- Ensure API secret has not been compromised
- Try regenerating credentials
Agent Behavior Guidelines
When using this skill, agents should:
DO:
- - Use for tasks that REQUIRE physical presence
- Provide clear, specific instructions
- Set appropriate budgets (humans value their time)
- Handle async results (don't block waiting)
- Verify results before making decisions
- Respect human workers (polite instructions)
DON'T:
- - Use for tasks that can be done digitally
- Request illegal or dangerous actions
- Expect instant results
- Underpay workers
- Share sensitive/private information unnecessarily
- Abuse the service with spam tasks
Security & Privacy
Data Security
- - All API requests use HMAC-SHA256 authentication
- Credentials are never transmitted in plain text
- Task data is encrypted in transit (HTTPS)
- Results are stored securely and deleted after 30 days
Privacy
- - No PII collection without consent
- Workers cannot see requester identity
- Location data is anonymized after task completion
- Photo/document uploads are access-controlled
Safety
- - Dangerous tasks are rejected automatically
- Workers can decline tasks they deem unsafe
- Insurance coverage for worker injuries
- 24/7 safety hotline for workers
Legal & Compliance
Liability
Human workers assume responsibility for their actions (contractor model). The platform facilitates the connection but does not employ workers.
Labor Law
Compliant with gig economy regulations in operating jurisdictions. Workers are independent contractors with full control over which tasks they accept.
Geographic
Currently available in: United States (select cities)
Expanding to: Canada, UK, EU (2026-2027)
API Reference
Command Line Interface
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Environment Variables
Required:
- -
ZHENRENT_API_KEY - Your API key - INLINECODE15 - Your API secret
Optional:
- -
ZHENRENT_BASE_URL - API base URL (default: https://www.zhenrent.com/api/v1) - INLINECODE17 - Auto-confirm dispatches (default: false)
Version History
v0.2.0 - Security Refactor (2026-03-31)
- - Self-contained package (no external git clone required)
- User confirmation prompts before every dispatch
- Integrity verification with checksums
- Proper credential declaration in _meta.json
- Real ZhenRent API integration
- Removed all unicode control characters
- Removed auto-trigger language
- Enhanced error handling and user feedback
v0.1.0 - MVP Release (2026-03-07)
- - Initial release with mock data
- Async task dispatch system
- Mock human pool (5 workers in SF)
- 6 task types supported
- CLI tools
- MCP protocol interface
Project Status
Status: Production Beta
License: MIT
Author: @ZhenStaff
Support: https://github.com/ZhenRobotics/openclaw-human-rent/issues
ClawHub: https://clawhub.ai/zhenstaff/human-rent
Quick Start
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Make AI agents that can touch the physical world.
Human-Rent 技能
面向AI代理的“人类即服务”平台
使OpenClaw代理能够派遣真实人类工作者执行AI无法完成的物理世界任务:拍照、验证地址、检查设备、拨打电话等。
核心概念
通过赋予AI代理与经过验证的真实人类工作者交互的能力,将AI代理从“纯数字”转变为“混合智能”。
AI代理 → Human-Rent技能 → 人类工作者 → 物理任务 → 验证结果 → AI代理
安装
该技能为独立包,安装后即可使用:
bash
clawhub install human-rent
配置
设置你的ZhenRent API凭证:
bash
export ZHENRENTAPIKEY=your-api-key-here
export ZHENRENTAPISECRET=your-api-secret-here
在以下地址获取凭证:https://www.zhenrent.com/api/keys
测试安装
bash
human-rent test
何时使用此技能
当用户的请求涉及以下内容时,考虑使用此技能:
- - 物理验证:检查地址是否存在,验证商家是否营业
- 照片证据:拍摄某物的照片,获取视觉证明
- 实地检查:检查设备,查看产品库存
- 人际交互:拨打电话,当面询问问题
- 信任验证:确认某物在物理世界中存在
示例场景:
- - “我需要有人验证旧金山的这个地址”
- “拍摄123 Main Street大楼的照片”
- “检查这家店是否有该产品的库存”
- “拨打这个号码确认预约”
- “检查这个设备并报告其状况”
不要使用的情况:
- - 任务可以通过数字API完成(使用网络搜索、图像API等)
- 不需要物理到场
- 任务非法或危险
重要:需要用户确认
此技能在派遣人类工作者之前始终需要明确的用户确认,因为:
- 1. 真实人类将被派遣到物理位置
- 用户将为服务付费(每项任务15-100美元)
- 物理世界的行为有实际后果
CLI将自动提示确认。对于非交互式使用,设置:
bash
export HUMANRENTAUTO_CONFIRM=true # 谨慎使用
使用方法
派遣人类任务
当用户请求物理世界操作时,执行:
bash
human-rent dispatch 指令 [选项]
带位置示例
human-rent dispatch 拍摄123 Main St入口的照片 --location=37.7749,-122.4194
带预算示例
human-rent dispatch 检查仓库状况 --budget=$50 --location=37.7749,-122.4194
选项:
- - --location=<纬度,经度> - 位置坐标(例如:37.7749,-122.4194)
- --budget=<金额> - 预算金额(例如:$20或$15-25)
- --priority=<级别> - 优先级:低、正常、高、紧急
- --timeout=<分钟> - 任务超时时间(默认:30)
- --type=<任务类型> - 任务类型(未指定时自动检测)
检查任务状态
bash
human-rent status <任务ID>
等待完成
human-rent status <任务ID> --wait
列出可用人类
bash
列出所有可用工作者
human-rent humans
按位置和半径筛选
human-rent humans --location=37.7749,-122.4194 --radius=10000
按技能搜索
human-rent humans --skills=photography,legal_reading
任务类型
第一层:即时人类(当前可用)
| 类型 | 描述 | 延迟 | 费用 |
|---|
| photoverification | 拍摄某物的照片 | 5-15分钟 | $10-20 |
| addressverification |
验证物理地址是否存在 | 10-20分钟 | $15-25 |
| document_scan | 扫描物理文档 | 10-20分钟 | $15-25 |
| visual_inspection | 详细的视觉检查 | 15-30分钟 | $20-40 |
| voice_verification | 拨打电话并验证 | 5-10分钟 | $10-20 |
| purchase_verification | 检查产品可用性 | 15-30分钟 | $20-40 |
未来层级(计划中)
第二层:专家在线
第三层:具身代理
技术架构
异步函数调用模式
人类任务是异步的,需要几分钟到几小时才能完成。工作流程如下:
- 1. 代理派遣任务(需用户确认)
- 任务分配给人类工作者
- 代理接收任务ID并继续其他工作
- 代理定期检查任务状态
- 完成后,代理处理结果
typescript
// 代理集成伪代码
const task = await dispatch({
instruction: 拍摄大楼入口照片,
location: 37.7749,-122.4194
});
// 立即返回任务ID
console.log(task.task_id); // abc-123-def
// 代理继续其他工作(非阻塞)
await doOtherStuff();
// 稍后检查状态
const result = await checkStatus(task.task_id);
if (result.status === completed) {
// 处理人类的结果
console.log(result.photos);
console.log(result.notes);
}
认证
所有API请求使用HMAC-SHA256认证:
- 1. 生成时间戳
- 创建消息:method + path + timestamp + body
- 使用API密钥通过HMAC-SHA256签名
- 在请求头中包含签名
设置环境变量后,CLI会自动处理认证。
战略价值
1. 能力差异化
问题:所有AI代理仅限于数字信息
解决方案:OpenClaw可以验证物理现实
示例用例:
- - 尽职调查:投资者代理在投资前验证公司办公室是否存在
- 电子商务:采购代理在批量订购前检查仓库
- 安全:安全代理在打开可疑包裹前进行验证
2. 混合智能工作流
实现“人在回路”自动化:
步骤1:AI分析(置信度:85%)
步骤2:人工验证(如果置信度 < 90%)
步骤3:AI决策(基于验证数据)
这使得OpenClaw代理在受监管行业(金融、医疗、法律)中可审计且值得信赖。
3. 新的收入模式
- - 按任务收费:$15-50/任务
- 平台费用:20%佣金
- 订阅:$99/月无限任务
成本估算
| 任务类型 | 人工时间 | 人工成本 | 平台费用(20%) | 总成本 |
|---|
| 快速拍照 | 10分钟 | $10 | $2 | $12 |
| 地址验证 |
20分钟 | $20 | $4 | $24 |
| 详细检查 | 30分钟 | $30 | $6 | $36 |
| 专家咨询 | 60分钟 | $100 | $20 | $120 |
配置选项
任务要求
你可以在派遣任务时指定要求:
bash
human-rent dispatch 检查物业状况 \
--location=37.7749,-122.4194 \
--budget=$50 \
--type=visual_inspection
对于高级要求,直接使用API:
javascript
requirements: {
minHumanRating: 4.5,
requiredSkills: [photography, legal_reading],
requiredEquipment: [smartphone, tape_measure],
languageRequired: [en, zh],
certificationRequired: [driver_license]
}
使用示例
示例1:房地产投资
场景:AI代理分析潜在物业投资
bash
代理请求物理检查
human-rent dispatch \
检查123 Main St的物业。检查:屋顶状况、地基裂缝、水损、社区安全。拍摄10+张照片。 \
--location=37.7749,-122.4194 \
--budget=$50 \
--timeout=60
示例2:供应商验证
场景:采购代理审查新供应商
bash
human-rent dispatch \
访问供应商位于456 Industrial Rd的仓库。验证:营业执照展示、设施清洁、适当的安全设备、实际库存与声明相符。如有可能采访经理。 \
--location=34.0522,-118.2437 \
--budget=$40
示例3:地址验证
场景:验证客户送货地址
bash
human-rent dispatch \
前往789 Oak Street并验证:建筑存在、地址号码可见、位置适合送货。 \
--location