← Back to Skills Marketplace
nicemaths123

Linkedin Buying Detector

by nicemaths123 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
90
Downloads
0
Stars
0
Active Installs
1
Versions
Install in OpenClaw
/install linkedin-buying-detector
Description
Detect LinkedIn hiring and growth signals to identify B2B companies ready to buy now and auto-generate personalized outreach messages.
README (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

Usage Guidance
What to consider before installing: - The SKILL.md expects an Apify API token (and implies an AI model key such as Anthropic/Claude plus CRM/Notion/Slack credentials) but the skill metadata declares none — treat that as a red flag. Only provide the Apify token or other credentials if you trust the skill source. - This skill instructs scraping LinkedIn and harvesting contact emails/decision‑maker info and will send that data to external services (Apify actors, AI provider, and potentially your CRM). Confirm legal/ToS/privacy implications for your use case and target jurisdiction. - Because the skill is instruction-only (no code files), there is no local code to audit; risk surfaces are network interactions. If you proceed, run it with least-privileged tokens (test accounts or read-only API keys), limit max_companies to a small number, and monitor outbound network activity. - Ask the publisher (or request updated metadata) to: (1) declare required env vars (APIFY_TOKEN, ANTHROPIC/CLAUDE key, and any integration tokens) in the registry, (2) document exactly which third‑party actors are run and what data they receive, and (3) provide an option to disable pushing results to external CRMs/webhooks. - If you cannot obtain that information, treat installation as higher risk and prefer sandboxed testing with throwaway credentials or decline.
Capability Analysis
Type: OpenClaw Skill Name: linkedin-buying-detector Version: 1.0.0 The skill is a lead generation tool designed to identify B2B buying signals by scraping LinkedIn via Apify. It functions as a set of instructions for an AI agent to orchestrate various Apify actors (e.g., 'curious_coder/linkedin-jobs-scraper') and use Claude AI for lead scoring and outreach generation. While it requests an Apify API token and contains affiliate links, its behavior is transparently aligned with its stated purpose and lacks indicators of malicious intent, data exfiltration, or harmful prompt injection.
Capability Assessment
Purpose & Capability
The skill's stated purpose (detect LinkedIn buying signals and generate outreach) matches the described workflow (scrape LinkedIn, company profiles, find decision‑makers, generate messages). However, the SKILL.md explicitly requires an Apify API token (and implies use of Claude/Anthropic and CRM/Notion/Airtable/Slack integrations) while the skill metadata declares no required env vars or primary credentials — that mismatch is unexpected and incoherent.
Instruction Scope
Runtime instructions tell the agent to scrape LinkedIn jobs/profiles, extract headcount and emails, call Apify actors, and pass company/profile data to Claude AI to generate outreach. The instructions include external data flows (Apify actors, Claude AI) and imply pushing results to Notion/Airtable/CRMs/Slack, but they do not constrain or document required credentials, nor do they describe safeguards for collecting/transmitting personal contact data. The scope expands beyond a simple local helper and involves network scraping and outbound data transmission.
Install Mechanism
This is an instruction-only skill with no install spec and no code files. That minimizes on‑disk installation risk; the runtime risk comes from network calls described in the instructions (Apify, Claude, and webhooks).
Credentials
The instructions require an Apify token and implicitly need an AI/model key (Claude/Anthropic) plus credentials for integrations (Notion, Airtable, HubSpot, Slack) to realize the listed outputs. The registry metadata lists no required environment variables or primary credential, so requested secrets are not declared — this is disproportionate and raises a risk that users will be asked for tokens at runtime without those needs being visible up front.
Persistence & Privilege
The skill does not request always:true, does not install persistent components, and does not modify other skills or system configs. Autonomous invocation is allowed (platform default) but not combined with elevated privileges here.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install linkedin-buying-detector
  3. After installation, invoke the skill by name or use /linkedin-buying-detector
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release — detect real-time B2B buying signals and generate AI-personalized outreach based on LinkedIn/job data. - Identifies companies with urgent buying intent using LinkedIn job postings and growth indicators. - Scores leads (Hot/Warm/Cold) based on hiring, tech, funding, and competitor signals. - Finds decision maker contacts and generates tailored email & LinkedIn messages using Claude AI. - Exports leads to CSV, JSON, Notion, Airtable, or CRM; integrates with Slack and email alerts. - Simple setup with clear inputs; leverages Apify-powered LinkedIn & news scraping.
Metadata
Slug linkedin-buying-detector
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Linkedin Buying Detector?

Detect LinkedIn hiring and growth signals to identify B2B companies ready to buy now and auto-generate personalized outreach messages. It is an AI Agent Skill for Claude Code / OpenClaw, with 90 downloads so far.

How do I install Linkedin Buying Detector?

Run "/install linkedin-buying-detector" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Linkedin Buying Detector free?

Yes, Linkedin Buying Detector is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Linkedin Buying Detector support?

Linkedin Buying Detector is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Linkedin Buying Detector?

It is built and maintained by nicemaths123 (@nicemaths123); the current version is v1.0.0.

💬 Comments