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Linkedin Buying Signal

作者 nicemaths123 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install linkedin-buying-signal
功能描述
Detect B2B buying intent by analyzing LinkedIn hiring, growth, and funding signals to generate scored leads with 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
Before installing or running this skill, consider the following: - Ask the author to clearly declare required credentials and how to supply them (Apify token, and any CRM/Notion/Slack/email credentials) as environment variables or documented inputs — do not paste secrets into free-text prompts. - Confirm how the Apify actors obtain LinkedIn/profile data: do they require a LinkedIn session cookie or authenticated access? If so, supplying such credentials grants broad access to your LinkedIn account; avoid sharing account cookies unless you fully trust and audit the actor. - Verify legal and privacy implications: the skill scrapes personal profiles and emails. Ensure compliance with LinkedIn's Terms of Service and local privacy laws (e.g., GDPR) before collecting/transmitting PII. - Request details on the exact Apify actors used (versions, code or run logs) and test with a very small, controlled dataset first (sandbox run, dummy inputs) to confirm behavior and outputs. - If you plan to push data to CRMs or email prospects, require that the skill explicitly list what credentials it needs and how it will store/transmit them; prefer short-lived tokens or user-controlled webhooks. - If you cannot obtain satisfactory answers about credential handling, data sources, or legal compliance, do not run the skill with real credentials or real personal data. Confidence note: assessment is medium because many issues could be innocuous documentation omissions (e.g., author expects apify_token as an input rather than an env var). However, the combination of unexplained credential needs, personal-data scraping, and unspecified integrations is enough to warrant caution.
功能分析
Type: OpenClaw Skill Name: linkedin-buying-signal Version: 1.0.0 The skill bundle (linkedin-buying-signal) is a sales intelligence tool designed to orchestrate web scraping via Apify to identify B2B leads on LinkedIn. While it requires a sensitive 'apify_token' and contains multiple affiliate links (e.g., to apify.com?fpr=dx06p), its functionality is clearly aligned with its stated purpose. There are no indicators of malicious intent, data exfiltration, or prompt injection attacks against the agent in SKILL.md.
能力评估
Purpose & Capability
The name/description (LinkedIn buying-signal detection + outreach) aligns with the SKILL.md: it describes scraping job posts/company pages, scoring intent, finding decision‑makers, and generating outreach. Using Apify actors and an LLM for scoring/outreach is coherent with the stated purpose.
Instruction Scope
The runtime instructions call multiple Apify actors to scrape LinkedIn, company pages, profiles, and Google News, and instruct the agent to extract decision‑maker emails and push data to CRMs/Notion. Those actions involve collecting personal data and transmitting it externally. The SKILL.md does not detail how protected/behind-login Linked LinkedIn content or emails will be accessed, nor does it include guidance on respecting rate limits, robots.txt, or legal/TOS/privacy constraints.
Install Mechanism
This is an instruction-only skill with no install spec or code files — lowest install risk. It relies on external Apify actors rather than installing binaries or downloading code.
Credentials
The instructions require an Apify API token (apify_token in the input) and reference pushing results to Notion/Airtable/HubSpot/email, but the skill metadata lists no required environment variables, no primary credential, and no config paths. That mismatch is problematic: the skill will need credentials for Apify and for downstream integrations, yet it doesn't declare them or explain where or how to supply them securely. The skill also implies harvesting emails/contacts but doesn't explain consent or lawful basis for collecting/transferring that personal data.
Persistence & Privilege
The skill does not request always:true and is user-invocable; autonomous invocation is allowed (platform default). It does not declare any ability to modify other skills or system config. No elevated persistence is requested.
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-buying-signal
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /linkedin-buying-signal 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. - Detects real-time buying signals on LinkedIn, such as hiring trends, tech stack changes, and funding rounds. - Aggregates company data (growth, signals, decision makers) and scores leads by intent (Hot / Warm / Cold). - Generates hyper-personalized AI outreach emails and LinkedIn messages for decision makers. - Outputs structured results (CSV, JSON, Notion/CRM ready) for targeted sales outreach. - Integrates with Slack, Notion, Airtable, HubSpot, and email for workflow automation. - Includes setup instructions, best practices, and clear cost/volume estimates.
元数据
Slug linkedin-buying-signal
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 Buying Signal 是什么?

Detect B2B buying intent by analyzing LinkedIn hiring, growth, and funding signals to generate scored leads with personalized outreach messages. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 83 次。

如何安装 Linkedin Buying Signal?

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

Linkedin Buying Signal 是免费的吗?

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

Linkedin Buying Signal 支持哪些平台?

Linkedin Buying Signal 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 Buying Signal?

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

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