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Lead Guardian
by
jonbarnato
· GitHub ↗
· v1.0.0
· MIT-0
87
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Install in OpenClaw
/install lead-guardian
Description
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.
README (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
Usage Guidance
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.
Capability Tags
Capability Assessment
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.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install lead-guardian - After installation, invoke the skill by name or use
/lead-guardian - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial publish — AI lead response and qualification skill
Metadata
Frequently Asked Questions
What is Lead Guardian?
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. It is an AI Agent Skill for Claude Code / OpenClaw, with 87 downloads so far.
How do I install Lead Guardian?
Run "/install lead-guardian" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Lead Guardian free?
Yes, Lead Guardian is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Lead Guardian support?
Lead Guardian is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Lead Guardian?
It is built and maintained by jonbarnato (@jonbarnato); the current version is v1.0.0.
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