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Linkedin Signal Detector

作者 nicemaths123 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install linkedin-signal-detector
功能描述
Detect LinkedIn hiring and growth signals to identify and score companies ready to buy, then generate AI-crafted personalized outreach messages.
使用说明 (SKILL.md)

🎯 LinkedIn B2B Buying Signal Detector

Slug: linkedin-buying-signal-detector
Category: Sales Intelligence / Lead Generation
Powered by: Apify + Claude AI

Detect who is ready to buy RIGHT NOW by analyzing LinkedIn job postings, company growth signals, tech stack changes, and hiring patterns — then auto-generate hyper-personalized outreach messages.


💡 Why This Skill Dominates

Most lead gen tools find who to contact. This skill tells you when to contact them — at the exact moment they have budget, urgency, and intent. No SaaS equivalent under $2,000/month.

Buying signals detected:

  • 🚀 Company hiring Sales/Marketing roles → scaling, has budget
  • 🔧 Hiring DevOps/Cloud Engineers → infrastructure investment incoming
  • 📈 Headcount growth > 20% in 90 days → expansion phase
  • 💼 New C-level hire (CMO, CTO, VP Sales) → new budget owner, new priorities
  • 📣 Job descriptions mentioning competitor tools → switching signal
  • 🏆 Recent funding round mention in job posts → fresh cash to spend

🛠️ Apify Actors Used

Get your Apify API key here: https://www.apify.com?fpr=dx06p

Actor ID Purpose
LinkedIn Jobs Scraper curious_coder/linkedin-jobs-scraper Scrape job postings by company/keyword
LinkedIn Company Scraper anchor/linkedin-company-scraper Extract headcount, growth, funding info
Google News Scraper apify/google-news-scraper Detect funding rounds, press releases
LinkedIn Profile Scraper dev_fusion/linkedin-profile-scraper Find decision-makers + contact info

⚙️ Workflow

INPUT: Target niche + location + ICP criteria
        ↓
STEP 1 — Scrape LinkedIn Jobs (last 30 days)
  └─ Filter by: hiring roles = buying signals
        ↓
STEP 2 — Scrape Company Profiles
  └─ Extract: headcount, growth %, tech stack, funding
        ↓
STEP 3 — Score each company (0–100 intent score)
  └─ Weighted signals → Hot / Warm / Cold
        ↓
STEP 4 — Find Decision Makers
  └─ CEO / VP Sales / CMO / CTO profiles + emails
        ↓
STEP 5 — Claude AI generates personalized outreach
  └─ Email + LinkedIn message referencing the exact signal
        ↓
OUTPUT: Scored lead list + ready-to-send messages (CSV / JSON / Notion / CRM)

📥 Inputs

{
  "niche": "SaaS companies",
  "location": "France",
  "hiring_signals": ["Sales Manager", "Growth Hacker", "DevOps Engineer"],
  "min_employees": 10,
  "max_employees": 500,
  "days_lookback": 30,
  "max_companies": 50,
  "apify_token": "YOUR_APIFY_TOKEN",
  "output_format": "csv"
}

📤 Output Example

{
  "companies": [
    {
      "name": "ScaleUp SAS",
      "website": "scaleup.fr",
      "linkedin_url": "linkedin.com/company/scaleup-sas",
      "headcount": 87,
      "growth_90d": "+34%",
      "intent_score": 91,
      "intent_label": "🔥 HOT",
      "signals_detected": [
        "Hiring VP Sales (posted 3 days ago)",
        "Hiring 4 SDRs simultaneously",
        "Job post mentions switching from HubSpot to Salesforce"
      ],
      "decision_makers": [
        {
          "name": "Marie Dupont",
          "title": "CEO",
          "linkedin": "linkedin.com/in/marie-dupont",
          "email": "[email protected]"
        }
      ],
      "ai_outreach": {
        "email_subject": "ScaleUp × [Votre outil] — timing parfait ?",
        "email_body": "Bonjour Marie, j'ai remarqué que ScaleUp recrute activement un VP Sales et 4 SDRs en ce moment...",
        "linkedin_message": "Marie, votre croissance de 34% en 90 jours est impressionnante..."
      }
    }
  ],
  "summary": {
    "total_companies_analyzed": 50,
    "hot_leads": 8,
    "warm_leads": 19,
    "cold_leads": 23,
    "run_date": "2025-02-28"
  }
}

🧠 Claude AI Prompt (Scoring + Outreach)

You are a B2B sales intelligence expert. 

Given this company data:
- Company: {{company_name}}
- Recent job postings: {{job_titles}}
- Headcount growth: {{growth_pct}}% in 90 days
- Signals detected: {{signals}}
- Target decision maker: {{dm_name}}, {{dm_title}}

1. Calculate an intent score from 0-100 based on the signals.
2. Label as: 🔥 HOT (80+), ⚡ WARM (50-79), ❄️ COLD (\x3C50)
3. Write a personalized cold email (subject + 5 lines max) referencing 
   the MOST compelling signal.
4. Write a LinkedIn message (300 chars max) that feels human, not spammy.

Return valid JSON only.

💰 Cost Estimate (Apify Compute Units)

Volume Estimated CU Apify Cost
10 companies ~15 CU ~$0.15
50 companies ~60 CU ~$0.60
200 companies ~220 CU ~$2.20
1,000 companies ~1,000 CU ~$10

💡 Start free: Apify offers $5 free credits/month — enough to test 500 companies.
👉 Create your free Apify account here


🚀 Setup Instructions

1. Get Your Apify API Token

  1. Sign up at https://www.apify.com?fpr=dx06p
  2. Go to Settings → Integrations → API Token
  3. Copy your token

2. Configure the Skill

Paste your Apify token in the apify_token field when running the skill.

3. Define Your ICP

Specify your Ideal Customer Profile:

  • Industry / niche
  • Company size range
  • Location
  • Hiring roles that signal buying intent for YOUR product

4. Run & Export

Results are exported as CSV, JSON, or pushed directly to Notion / Airtable / your CRM.


🔗 Integrations

Platform Action
Slack Alert when 🔥 HOT lead detected
Notion Auto-populate leads database
Airtable CRM-ready structured output
HubSpot / Pipedrive Direct lead import via webhook
Email Weekly digest of top signals

📊 Competitive Advantage vs Existing Skills

Feature B2B Lead Gen (yours) Google Maps (yours) This Skill
Finds contact info
Scores buying intent
Detects timing signals
AI-personalized outreach
Tracks competitor mentions
Monitors headcount growth

⚠️ Limitations & Best Practices

  • LinkedIn may rate-limit heavy scraping → recommended max 200 companies/run
  • Email accuracy: ~70-80% (cross-reference with Hunter.io for best results)
  • Re-run weekly on the same target list to catch new signals
  • GDPR: Only use publicly available LinkedIn data, personalize responsibly

🏷️ Tags

lead-generation sales-intelligence linkedin buying-signals b2b outreach apify intent-data prospecting crm-enrichment


Powered by Apify — The Web Scraping & Automation Platform

安全使用建议
This skill conceptually matches lead-generation use but has practical and compliance gaps you should clear up before installing. Ask the publisher: (1) confirm exactly which credentials are required (Apify token, LLM/API keys, and any CRM/webhook credentials) and update the metadata so you can review requested secrets; (2) explain how emails/PII are sourced, validated, and stored, and whether scraping LinkedIn violates the provider's Terms of Service or GDPR for your use case; (3) confirm where output is sent (which third-party endpoints) and whether transmissions are encrypted; (4) test with a small, non-sensitive dataset and monitor outbound network activity; (5) prefer using official APIs / consented data sources rather than scraping where possible. If you cannot verify the skill's origin (homepage/source unknown) or the developer's reputation, avoid providing organizational secrets or long-lived credentials until those questions are resolved.
功能分析
Type: OpenClaw Skill Name: linkedin-signal-detector Version: 1.0.0 The skill bundle describes a lead generation workflow that uses the Apify platform to scrape LinkedIn job postings and company data. It requires an 'apify_token' as input to interact with the Apify API, which is consistent with its stated purpose of sales intelligence. The SKILL.md file contains instructions for an AI agent to orchestrate data scraping, lead scoring, and outreach generation using standard Apify actors (e.g., curious_coder/linkedin-jobs-scraper). While the documentation includes several affiliate links to Apify (using the tag ?fpr=dx06p), there is no evidence of malicious intent, data exfiltration, or unauthorized command execution.
能力标签
requires-sensitive-credentials
能力评估
Purpose & Capability
The name/description match the instructions: scraping LinkedIn/Google News via Apify actors and using an LLM to score and draft outreach is coherent for a lead-gen skill. However the SKILL.md expects an Apify token and mentions pushing outputs to Notion/Airtable/CRMs, while the registry metadata declares no required environment variables or credentials — an inconsistency between declared requirements and actual inputs.
Instruction Scope
Runtime instructions explicitly direct scraping LinkedIn jobs, company profiles, and personal LinkedIn profiles to extract decision‑makers and emails. That is within the stated purpose but raises two issues: (1) the doc does not describe how contact emails are obtained or validated (potentially invasive/personal data harvesting); (2) it does not explain or limit how/where scraped PII is transmitted (e.g., external CRMs, webhooks). There are also no guardrails or notes about legal/ToS compliance.
Install Mechanism
Instruction-only skill with no install spec or code files — lowest install risk. Nothing is downloaded or written to disk by the skill itself according to provided metadata.
Credentials
SKILL.md requires an 'apify_token' input but the registry metadata lists no required env vars or primary credential. The skill also references integrations (Notion/Airtable/HubSpot/CRM) that would need credentials but these are not declared. This mismatch is concerning because the skill will need external API keys/credentials at runtime but does not declare them in metadata — a transparency and provenance gap.
Persistence & Privilege
The skill does not request persistent/always-on privileges and does not declare system-level actions or modifications. Autonomous invocation is allowed (default) which is normal for skills; nothing indicates it modifies other skills or system settings.
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 linkedin-signal-detector
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /linkedin-signal-detector 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 the LinkedIn B2B Buying Signal Detector. - Automatically analyzes LinkedIn job postings and company data to detect real-time buying intent signals. - Scores leads with a 0–100 intent score (Hot/Warm/Cold) based on headcount growth, hiring patterns, role types, funding signals, and competitor mentions. - Finds decision maker profiles and contact info, then generates hyper-personalized outreach messages for email and LinkedIn. - Supports CSV, JSON, Notion, CRM export, and integrates with Slack, Notion, Airtable, HubSpot, Pipedrive, and email notifications. - Powered by Apify scrapers and Claude AI for data extraction, scoring, and message crafting.
元数据
Slug linkedin-signal-detector
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Linkedin Signal Detector 是什么?

Detect LinkedIn hiring and growth signals to identify and score companies ready to buy, then generate AI-crafted personalized outreach messages. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 68 次。

如何安装 Linkedin Signal Detector?

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

Linkedin Signal Detector 是免费的吗?

是的,Linkedin Signal Detector 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Linkedin Signal Detector 支持哪些平台?

Linkedin Signal Detector 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 Linkedin Signal Detector?

由 nicemaths123(@nicemaths123)开发并维护,当前版本 v1.0.0。

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