← 返回 Skills 市场
aiwithabidi

Lead Gen Pipeline

作者 aiwithabidi · GitHub ↗ · v1.0.0
cross-platform ✓ 安全检测通过
297
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install lead-gen-pipeline
功能描述
Automated lead generation pipeline with AI-powered lead scoring and personalized follow-up generation. Score leads 0-100 with reasoning, generate context-awa...
使用说明 (SKILL.md)

Lead Gen Pipeline

AI-powered lead generation pipeline. Score leads intelligently, generate personalized follow-ups, and manage your sales pipeline.

Quick Start

export OPENROUTER_API_KEY="your-key"

# Score a lead
python3 {baseDir}/scripts/lead_scorer.py '{"name":"Jane Smith","company":"Acme Corp","title":"VP Marketing","source":"webinar","actions":["downloaded whitepaper","visited pricing page 3x","opened 5 emails"]}'

# Generate follow-up
python3 {baseDir}/scripts/followup_generator.py '{"name":"Jane Smith","company":"Acme Corp","context":"Attended our AI webinar, downloaded whitepaper","stage":"warm","tone":"professional"}'

Lead Scoring

The AI scorer evaluates leads on multiple dimensions:

Factor Weight Description
Fit 30% Does the lead match your ICP? (title, company size, industry)
Intent 30% Behavioral signals (page visits, downloads, email engagement)
Engagement 20% How actively are they interacting? (recency, frequency)
Source Quality 20% Where did they come from? (referral > webinar > cold)

Score Ranges

  • 80-100: 🔥 Hot — reach out immediately, high buying intent
  • 60-79: 🟡 Warm — nurture with targeted content, book a call
  • 40-59: 🟠 Cool — add to drip sequence, monitor engagement
  • 0-39: 🔵 Cold — low priority, long-term nurture only
# Score with custom ICP
python3 {baseDir}/scripts/lead_scorer.py '{"name":"...","company":"...","icp":{"industries":["SaaS","fintech"],"minEmployees":50,"titles":["VP","Director","C-suite"]}}'

Follow-Up Generation

Generate personalized follow-up messages for any pipeline stage:

# Professional follow-up after demo
python3 {baseDir}/scripts/followup_generator.py '{
  "name": "Jane Smith",
  "company": "Acme Corp",
  "context": "Had a 30-min demo, interested in enterprise plan, concerned about onboarding time",
  "stage": "post-demo",
  "tone": "professional",
  "channel": "email"
}'

# Casual SMS check-in
python3 {baseDir}/scripts/followup_generator.py '{
  "name": "Mike",
  "context": "Met at conference, exchanged cards, talked about AI automation",
  "stage": "initial",
  "tone": "casual",
  "channel": "sms"
}'

# Urgent closing message
python3 {baseDir}/scripts/followup_generator.py '{
  "name": "Sarah Johnson",
  "company": "TechFlow",
  "context": "Proposal sent 5 days ago, no response, deal worth $25k, quarter ending",
  "stage": "closing",
  "tone": "urgent",
  "channel": "email"
}'

Supported Tones

  • professional — formal business communication
  • casual — friendly, conversational
  • urgent — time-sensitive, action-oriented
  • friendly — warm, relationship-focused
  • consultative — expert advice framing

Supported Channels

  • email — full email with subject line
  • sms — short, punchy (\x3C 160 chars)
  • whatsapp — conversational, emoji-friendly
  • linkedin — professional networking tone

Pipeline Stages

  • initial — first contact / cold outreach
  • warm — engaged but no meeting yet
  • booked — meeting/demo scheduled
  • post-demo — after initial call/demo
  • proposal — proposal sent
  • closing — negotiation / final decision
  • revival — re-engaging cold/lost lead

Cold Outreach Templates

The AIDA Framework

  1. Attention — Hook with relevant pain point
  2. Interest — Show you understand their world
  3. Desire — Paint the outcome
  4. Action — Clear, low-friction CTA

Outreach Sequences

Day 1: Initial value-first email Day 3: Follow-up with case study / social proof Day 7: Different angle (video, voice note, meme) Day 14: Break-up email ("Should I close your file?")

Generate any of these:

python3 {baseDir}/scripts/followup_generator.py '{"name":"...","stage":"initial","sequence_step":1}'
python3 {baseDir}/scripts/followup_generator.py '{"name":"...","stage":"initial","sequence_step":4}'

CRM Integration Patterns

With GHL (GoHighLevel)

# 1. Score incoming lead
SCORE=$(python3 {baseDir}/scripts/lead_scorer.py '{"name":"...","source":"facebook_ad"}')

# 2. Create contact in GHL with score tag
python3 ../ghl-crm/{baseDir}/scripts/ghl_api.py contacts create '{"firstName":"...","tags":["score-85","hot-lead"]}'

# 3. Add to appropriate pipeline stage
python3 ../ghl-crm/{baseDir}/scripts/ghl_api.py opportunities create '{"pipelineId":"...","stageId":"hot-stage-id","contactId":"..."}'

# 4. Generate and send follow-up
MSG=$(python3 {baseDir}/scripts/followup_generator.py '{"name":"...","stage":"warm","channel":"sms"}')
python3 ../ghl-crm/{baseDir}/scripts/ghl_api.py conversations send-sms \x3CcontactId> "$MSG"

With Any CRM

The scripts output JSON — pipe into any CRM API wrapper. Lead scores include reasoning that can be stored as CRM notes.

Response Handling

When a lead replies, re-score with updated context:

python3 {baseDir}/scripts/lead_scorer.py '{"name":"Jane","company":"Acme","actions":["replied to email","asked about pricing","requested demo"]}'

Then generate contextual response:

python3 {baseDir}/scripts/followup_generator.py '{"name":"Jane","context":"She asked about pricing and wants a demo","stage":"warm","tone":"professional"}'

Credits

Built by M. Abidi | agxntsix.ai YouTube | GitHub Part of the AgxntSix Skill Suite for OpenClaw agents.

📅 Need help setting up OpenClaw for your business? Book a free consultation

安全使用建议
This skill is internally consistent, but note: using it will send lead data (names, company, context, behavioral signals, etc.) to OpenRouter (openrouter.ai). Before installing or running, ensure you have the right to send any personally identifiable or sensitive customer data to a third-party LLM. Use a dedicated OpenRouter API key with minimal permissions, test with scrubbed/example data first, and verify any CRM integration commands (the SKILL.md shows example paths to external crm wrappers that are not included). Also verify the homepage/author if provenance matters to you. If you need stricter data controls, consider running a local/private LLM or redacting PII before calling the API.
功能分析
Type: OpenClaw Skill Name: lead-gen-pipeline Version: 1.0.0 The lead-gen-pipeline skill bundle is a legitimate toolset for AI-driven lead scoring and message generation. The Python scripts (followup_generator.py and lead_scorer.py) use the OpenRouter API to process lead data and return structured JSON results, adhering strictly to their stated purpose. No evidence of data exfiltration, unauthorized command execution, or malicious prompt injection was found.
能力评估
Purpose & Capability
Name/description match the included Python scripts and SKILL.md. The only required credential is OPENROUTER_API_KEY which is needed to call the OpenRouter LLM API used by both scripts. No unrelated services, binaries, or config paths are requested.
Instruction Scope
SKILL.md instructs running the two included scripts with JSON input; the scripts only build JSON prompts and POST them to openrouter.ai. There are no instructions to read system files, secrets beyond OPENROUTER_API_KEY, or to exfiltrate data to unexpected endpoints. Example CRM integration lines reference external crm wrappers but are examples and not executed by the skill itself.
Install Mechanism
This is instruction-only / script-based with no install spec. Nothing is downloaded or installed by the skill, so there is no high-risk install mechanism.
Credentials
Only OPENROUTER_API_KEY is required (declared as primaryEnv). That is proportional: both scripts embed the key in Authorization headers to call openrouter.ai. No extra tokens, passwords, or unrelated env vars are requested.
Persistence & Privilege
The skill does not request always: true, does not modify other skills or system configuration, and is user-invocable. It runs only when the user runs the scripts.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install lead-gen-pipeline
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /lead-gen-pipeline 触发
  4. 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 release of lead-gen-pipeline. - Automates lead scoring (0-100) with AI, providing reasoning for each score. - Generates personalized follow-ups in multiple tones (professional, casual, urgent, etc.) and channels (email, SMS, WhatsApp, LinkedIn). - Integrates seamlessly with any CRM via JSON output; includes step-by-step examples for GoHighLevel. - Supports stage-aware follow-up generation and cold outreach sequencing (AIDA, multi-step sequences). - Designed for easy use in sales automation, cold outreach, and pipeline management.
元数据
Slug lead-gen-pipeline
版本 1.0.0
许可证
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Lead Gen Pipeline 是什么?

Automated lead generation pipeline with AI-powered lead scoring and personalized follow-up generation. Score leads 0-100 with reasoning, generate context-awa... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 297 次。

如何安装 Lead Gen Pipeline?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install lead-gen-pipeline」即可一键安装,无需额外配置。

Lead Gen Pipeline 是免费的吗?

是的,Lead Gen Pipeline 完全免费(开源免费),可自由下载、安装和使用。

Lead Gen Pipeline 支持哪些平台?

Lead Gen Pipeline 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 Gen Pipeline?

由 aiwithabidi(@aiwithabidi)开发并维护,当前版本 v1.0.0。

💬 留言讨论