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Lead Guardian
作者
jonbarnato
· GitHub ↗
· v1.0.0
· MIT-0
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版本数
在 OpenClaw 中安装
/install lead-guardian
功能描述
AI-powered real estate lead response and qualification via SMS, email, or CRM to instantly engage, qualify, and route hot buyer and seller leads for agents.
使用说明 (SKILL.md)
Lead Guardian — Real Estate Lead Response Skill
AI-powered lead response and qualification for real estate agents.
Description
Lead Guardian helps real estate agents respond to leads instantly, qualify them automatically, and route hot leads for immediate follow-up. Works via SMS, email, or CRM webhook integration.
Capabilities
- Instant Response — Reply to new leads within 60 seconds
- AI Qualification — Extract buying/selling intent, timeline, pre-approval status, price range
- Hot Lead Detection — Identify ready-to-buy leads and alert agents immediately
- Conversation Tracking — Full history of lead interactions
- CRM Integration — Connect with Follow Up Boss, KW Command, and others
Use Cases
- After-Hours Coverage — Respond to leads when you're unavailable
- Lead Qualification — Filter tire-kickers from serious buyers
- Speed to Lead — Beat competitors with instant response
- Consistent Follow-Up — Never miss a lead
Requirements
- Twilio account (for SMS)
- OpenRouter API key (for AI)
- Optional: CRM webhook URL
Quick Start
# Install dependencies
pip install flask twilio requests python-dotenv
# Configure
export TWILIO_ACCOUNT_SID="your_sid"
export TWILIO_AUTH_TOKEN="your_token"
export TWILIO_PHONE_NUMBER="+1xxxxxxxxxx"
export OPENROUTER_API_KEY="your_key"
export AGENT_PHONE="+1xxxxxxxxxx"
# Run
python app.py
Configuration
Environment Variables
| Variable | Required | Description |
|---|---|---|
| TWILIO_ACCOUNT_SID | Yes | Twilio account SID |
| TWILIO_AUTH_TOKEN | Yes | Twilio auth token |
| TWILIO_PHONE_NUMBER | Yes | Your Twilio phone number |
| OPENROUTER_API_KEY | Yes | For AI responses |
| AGENT_PHONE | No | Phone to alert for hot leads |
Hot Lead Criteria
A lead is flagged as "hot" when:
- Timeline is "immediate" or "1-3 months"
- Pre-approved for mortgage
- Explicitly requests an agent
Qualification Questions
The AI naturally extracts:
- Direction — Buying, selling, or both
- Timeline — When they want to move
- Pre-approval — Mortgage status (if buying)
- Price Range — Budget (if buying)
API Endpoints
| Endpoint | Method | Description |
|---|---|---|
/sms |
POST | Twilio webhook for incoming SMS |
/api/leads |
GET | List all leads |
/api/leads/:id/messages |
GET | Get conversation history |
/api/leads/:id/handoff |
POST | Mark lead as handed off |
/ |
GET | Admin dashboard |
Cost
~$30/month for 500 leads
- Twilio number: $1/month
- SMS (1,000 messages): $10
- Claude Haiku API: $15-20
Files
lead-guardian/
├── SKILL.md # This file
├── app.py # Main Flask application
├── leads.db # SQLite database (created on run)
└── .env.example # Environment template
Credits
Built by KW Sacramento Metro AI Team.
License
MIT
安全使用建议
This implementation looks like a straightforward Twilio + OpenRouter lead autoresponder, but exercise caution before using it in production or on real credentials.
What to check before installing/running:
- Code completeness and authenticity: the provided app.py is truncated in the artifact you gave me. Get the full source from a trusted author or repository and review it before running.
- Endpoint authentication: confirm the admin dashboard and /api endpoints require authentication and that Twilio webhook requests are validated (Twilio request signature) to prevent spoofing. Do not expose the app to the public internet without HTTPS and auth.
- Credentials: only provide Twilio and OpenRouter API keys if you trust the source. Rotate keys after testing. Use least-privilege Twilio credentials if possible.
- Data persistence & privacy: the app writes leads.db in its directory. Verify data retention, backups, and who can access that file on the host. Consider running in an isolated container or VM.
- Behavior testing: run locally with dummy credentials first; observe outbound requests (which should be only to Twilio and openrouter.ai). Confirm there are no unexpected external endpoints in the full source.
- Hardcoded persona and defaults: the system prompt hardcodes an agent name and comments in the header reference "Jon's phone" — replace with neutral text and configuration variables if you deploy.
If you want, I can: (1) attempt to reconstruct the truncated portion if you paste the rest of app.py, (2) list concrete tests to run in a sandbox, or (3) produce a hardened checklist (webhook validation, auth for dashboard, DB encryption) to make this safe to run.
能力标签
能力评估
Purpose & Capability
Name/description, SKILL.md, and app.py align: the skill implements SMS lead handling, qualification, and routing using Twilio and OpenRouter (Claude model). The requested environment variables (Twilio credentials, OpenRouter API key, optional AGENT_PHONE) are appropriate for the described functionality.
Instruction Scope
SKILL.md and app.py indicate the app will create a local SQLite DB (leads.db) and expose HTTP endpoints (including an admin dashboard). The manifest does not include .env.example or leads.db (they are listed in SKILL.md but not provided), and the shipped app.py is truncated in the provided content (the /sms handler is cut off), so behavior of the remainder of the code (dashboard, auth, /api endpoints, any webhook verification) is unknown. Exposing an unauthenticated admin dashboard or API would be a significant privacy/security risk. Also the system prompt hardcodes an agent identity (Jon Barnato) which leaks/locks the assistant persona and may be undesired.
Install Mechanism
No install spec; this is instruction + Python app. No external downloads or installers are included, so installation risk is limited to installing common Python packages per SKILL.md. That said, the top-of-file comment suggests packages (openai) that are not used; minor inconsistency but not an install-time risk.
Credentials
Declared environment variables (TWILIO_ACCOUNT_SID, TWILIO_AUTH_TOKEN, TWILIO_PHONE_NUMBER, OPENROUTER_API_KEY, optional AGENT_PHONE) are proportional to an SMS + AI lead responder. No unrelated credentials or surprising env access are requested.
Persistence & Privilege
The skill does not request always:true and does not declare unusual privileges. It creates a local leads.db file which persists lead data on disk; that's expected for the use case but you should verify file location and retention policy. Ensure the HTTP endpoints (dashboard, APIs) are protected before exposing to the internet.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install lead-guardian - 安装完成后，直接呼叫该 Skill 的名称或使用
/lead-guardian触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
Initial publish — AI lead response and qualification skill
元数据
常见问题
Lead Guardian 是什么？
AI-powered real estate lead response and qualification via SMS, email, or CRM to instantly engage, qualify, and route hot buyer and seller leads for agents. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 87 次。
如何安装 Lead Guardian？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install lead-guardian」即可一键安装，无需额外配置。
Lead Guardian 是免费的吗？
是的，Lead Guardian 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Lead Guardian 支持哪些平台？
Lead Guardian 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Lead Guardian？
由 jonbarnato（@jonbarnato）开发并维护，当前版本 v1.0.0。
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