Limited time · 90% off Premium Membership - claim $199 deal →
Asset Vault · Software Templates

Automate Lead Generation with AI Agent - OpenClaw Skill

Skill Structure lead-gen/├── SKILL.md (152 lines) ⭐ Core skill with quick start│   └── References 5 detailed guides│├── references/ (1,434 lines total)│   ├── filters.md (172 lines)│  ...

Automate Lead Generation with AI Agent - OpenClaw Skill
TypeSoftware Templates FormatOpenClaw
T
TypeSoftware Templates
S
SubtypeOpenClaw
C
CreatorJames Dabalus
I
IncludesAsset

Description

Skill Structure

 

lead-gen/

├── SKILL.md (152 lines) Core skill with quick start

   └── References 5 detailed guides

├── references/ (1,434 lines total)

   ├── filters.md (172 lines)

      └── Filter syntax, profiles, debugging

   ├── templates.md (230 lines)

      └── Email templates, A/B variants, personalization rules

   ├── discovery.md (270 lines)

      └── Search strategies, multi-source workflows, enrichment

   ├── configuration.md (401 lines)

      └── Config format, all settings, environment variables

   └── ethics.md (361 lines)

       └── Legal compliance (CAN-SPAM, GDPR, CASL), anti-spam, reputation

├── scripts/ (329 lines)

   ├── discover_leads.py (136 lines)

      └── Search filter enrich workflow

   └── send_outreach.py (193 lines)

       └── Render templates personalize send at scale

├── templates/ (28 lines)

   ├── cold_email_v1.txt

      └── Problem-focused pitch

   └── cold_email_v2.txt

       └── Opportunity-focused pitch

└── example-config.json

    └── Sample config to get started

Key Design Choices

SKILL.md under 500 lines — 152 lines of concise instructions
Details moved to references/ — Agent loads only what's needed
Scripts are executable — discover_leads.py and send_outreach.py ready to use
Multiple templates — A/B test variants built-in
Compliance-firstEthics.md covers CAN-SPAM, GDPR, CASL
Progressive disclosure — Quick start, then detailed guides as needed

How the Agent Uses It

1.           User asks: "Find CTOs at Series A SaaS startups"

2.           Agent reads: SKILL.md (152 lines of guidance)

3.           Agent references: discovery.md for search strategies, filters.md for criteria

4.           Agent runs: discover_leads.py to find + filter prospects

5.           User asks: "Now send outreach with personalization"

6.           Agent reads: templates.md for design, ethics.md for compliance

7.           Agent runs: send_outreach.py at throttled rate with personalization