| name | job-posting-intent |
| version | 1.1.0 |
| description | Detect buying intent from job postings. When a company posts a job in your problem area, they've allocated budget and are actively thinking about the problem. This skill finds those companies, qualifies them, extracts personalization context, and outputs everything to a Google Sheet. Does NOT do outreach — just delivers qualified leads with reasoning.
|
| tags | ["lead-generation","outreach"] |
Job Posting Intent Detection
Find companies that are hiring for roles related to the problem you solve. A job posting is a budget signal — the company has allocated money to solve a problem your product addresses.
Results are automatically exported to a Google Sheet with signal strength, decision-maker suggestions, outreach angles, and personalization context.
Why This Works
When a company posts a job, they've:
- Allocated budget (headcount is expensive)
- Acknowledged the problem exists
- Started actively solving it
If your product helps solve that problem faster, cheaper, or better than a hire alone, the timing is perfect.
Cost
Apify Actor: harvestapi/linkedin-job-search (pay-per-event)
| Component | Cost |
|---|
| Actor start (per run) | $0.001 |
| Per job result | $0.001 |
| Apify platform fee | +20% |
Typical run costs:
| Scenario | Titles | Jobs/title | Runs | Est. Cost |
|---|
| Quick scan | 3 | 25 | 3 | ~$0.09 |
| Standard | 5 | 25 | 5 | ~$0.16 |
| Deep search | 5 | 100 | 5 | ~$0.60 |
| Multi-location | 5×3 | 25 | 15 | ~$0.47 |
Google Sheet creation is free (uses Rube/Composio integration).
Always run --estimate-only first to see the Apify cost before executing.
Track usage: https://console.apify.com/billing
Setup
1. Apify API Token
export APIFY_API_TOKEN="apify_api_YOUR_TOKEN_HERE"
2. Install dependencies
pip3 install requests
3. Rube/Composio (for Google Sheets)
Google Sheet creation uses Rube MCP with Composio. The token is preconfigured.
If it stops working, update the RUBE_TOKEN env var or the default in search_jobs.py.
Usage
Step 1: Define your ICP and target titles
Think about it this way: "If a company is hiring for [role], it means they're investing in [problem area you solve]."
Examples:
- GTM agency: "Growth Marketing Manager", "SDR Manager", "RevOps Engineer", "GTM Engineer"
- AI dev tools: "AI Engineer", "ML Ops Engineer", "Prompt Engineer", "LLM Engineer"
- Sales automation: "SDR", "BDR Manager", "Sales Ops", "Revenue Operations"
Step 2: Estimate cost
python3 scripts/search_jobs.py \
--titles "GTM Engineer,SDR Manager,Head of Demand Gen" \
--locations "United States" \
--max-per-title 25 \
--estimate-only
Step 3: Run the search
The script searches LinkedIn Jobs, groups results by company, qualifies leads, and creates a Google Sheet automatically.
python3 scripts/search_jobs.py \
--titles "GTM Engineer,SDR Manager,RevOps Engineer" \
--locations "United States" \
--max-per-title 25
python3 scripts/search_jobs.py \
--titles "AI Engineer,ML Ops Engineer,Prompt Engineer" \
--locations "United States" \
--max-per-title 50 \
--sheet-name "AI Hiring Signals - Feb 2026"
python3 scripts/search_jobs.py \
--titles "GTM Engineer,Growth Marketing Manager,SDR Manager" \
--locations "United States" \
--relevance-keywords "gtm,growth,sdr,marketing,demand gen,revops"
python3 scripts/search_jobs.py \
--titles "GTM Engineer,SDR Manager" \
--locations "United States" \
--output results.json
python3 scripts/search_jobs.py \
--titles "GTM Engineer" \
--no-sheet --json
What the Script Does
- Searches LinkedIn Jobs for each title/location combination via Apify
- Groups results by company (deduplicates)
- Computes signal strength based on number of relevant postings + seniority
- Extracts personalization context from job descriptions (tech stack, growth signals, pain points)
- Suggests decision-maker title (one level above the hired role)
- Suggests outreach angle (accelerate / replace / multiply the hire)
- Creates a Google Sheet with all qualified leads
- Prints a console summary of all companies found
Options Reference
Required:
--titles Comma-separated job titles to search
Optional:
--locations Comma-separated locations (default: no filter)
--max-per-title Max jobs per title per location (default: 25)
--posted-limit Recency: 1h, 24h, week, month (default: week)
--output, -o Also save raw JSON to this file path
--json Print JSON output to console
--estimate-only Show cost estimate without running
--no-sheet Skip Google Sheet creation
--sheet-name Custom Google Sheet title (default: "Job Posting Intent Signals - {date}")
--relevance-keywords Comma-separated keywords to filter truly relevant postings
Google Sheet Columns
| Column | Description |
|---|
| Signal | HIGH / MEDIUM / LOW based on # postings + seniority |
| Company | Company name |
| Employees | Employee count |
| Industry | Company industry |
| Website | Company website |
| LinkedIn | Company LinkedIn URL |
| # Postings | Number of relevant job postings found |
| Job Titles | The actual job titles posted |
| Job URL | Link to the primary job posting |
| Location | Job location(s) |
| Decision Maker | Suggested title of person to contact |
| Outreach Angle | Accelerate / Replace / Multiply the hire |
| Tech Stack | Technologies mentioned in job descriptions |
| Growth Signals | Growth indicators (first hire, scaling, series stage) |
| Pain Points | Pain indicators (automate, optimize, manual processes) |
| Description | Company description snippet |
AI Agent Integration
When using this skill as an agent, the typical flow is:
- User describes their product and the types of roles that signal intent
- Agent runs
--estimate-only and confirms cost with user
- Agent runs the search (Google Sheet is created automatically)
- Agent shares the Google Sheet link with the user
- Agent provides a brief summary of top leads and why they're qualified
Example prompt:
"Find companies hiring growth marketers and SDRs in the US this week. These are signals they need GTM help. We sell AI-powered GTM systems to Series A-C B2B SaaS companies with 20-200 employees."
The agent should NOT:
- Do any outreach
- Send any emails or messages
- Contact anyone
The agent SHOULD:
- Present cost estimate before running
- Run the search (sheet is created automatically)
- Share the Google Sheet link
- Provide a brief summary of the top leads with reasoning
Outreach Angle Templates
The script auto-assigns an angle based on job posting context:
"Accelerate while you hire" — Best when: posting is recent, role is junior/mid
They're looking for someone to do X. Your product can deliver X outcomes while they ramp the hire.
"Replace the hire" — Best when: small company, "first hire" signals, building from scratch
They want the output of a [role] but may not need a full-time person if they use your product.
"Multiply the hire" — Best when: company is clearly scaling, multiple related roles
When their new hire starts, your product makes them 10x more effective from day one.
Troubleshooting
"No jobs found"
- Try broader titles (e.g., "marketing" instead of "demand generation specialist")
- Extend the time window:
--posted-limit month
- Remove location filter to search globally
"Too many irrelevant results"
- Use
--relevance-keywords to filter by title keywords
- LinkedIn's search is fuzzy — the grouping and qualification step helps filter
"Google Sheet creation failed"
- Check that Rube MCP is accessible (the token may have expired)
- Use
--no-sheet --json --output results.json to save results without a sheet
- You can create the sheet later with
scripts/create_sheet_mcp.py
High cost estimate
- Reduce
--max-per-title (25 is usually enough)
- Search fewer titles
- Use
--posted-limit 24h for a quick daily scan
Links
