This article provides a complete, practical walkthrough of the Wait Code Automation Webhook n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   **Title**:  
   TopSourcer: How to Automate LinkedIn Candidate Sourcing with n8n
   
   **Meta Description**:  
   Harness the power of AI and automation using n8n to find LinkedIn candidates with Boolean search. This guide explores the TopSourcer workflow that extracts LinkedIn profiles from Google and formats them into a Google Sheet.
   
   **Keywords**:  
   n8n workflow, LinkedIn sourcing automation, Boolean search automation, AI candidate sourcing, TopSourcer n8n, Google Sheets LinkedIn extractor, GPT-4 Boolean search, openAI API, Google search automation, LinkedIn scraper n8n
   
   ---
   
   # TopSourcer: How to Automate LinkedIn Candidate Sourcing with n8n
   
   Recruiting the perfect candidate starts with sourcing, but traditional methods can be slow, repetitive, and inefficient. What if you could automate the process of generating Boolean search queries, running Google searches, extracting LinkedIn profiles, and compiling the results into a spreadsheet — all using natural language input?
   
   Enter **TopSourcer**, an automated n8n workflow designed to do exactly that. By integrating OpenAI’s GPT capabilities, authenticated Google searches, and structured Google Sheets output, TopSourcer streamlines the initial sourcing process that every recruiter, hiring manager, or talent acquisition specialist faces on a daily basis.
   
   Let’s explore how this powerful automation works and what makes it a game-changer in the world of recruitment tech.
   
   ---
   
   ## The Purpose of TopSourcer
   
   TopSourcer transforms how recruiters find potential hires. It does this by:
   
   1. Accepting natural language job descriptions.
   2. Using OpenAI to generate a precise Boolean search string.
   3. Running an authenticated Google search limited to LinkedIn profiles.
   4. Extracting LinkedIn profile URLs from each result page.
   5. Compiling and organizing the results automatically into a structured Google Sheet.
   
   Not only does it save time, but it also reduces errors and ensures consistency in candidate sourcing.
   
   ---
   
   ## How TopSourcer Works: Step by Step
   
   ### 1. Natural Language Trigger
   
   The process begins with a chat-based trigger where a user inputs a job description or a desired candidate profile in plain English.
   
   - Node: `When chat message received`
   - Example Input: "I’m looking for a Senior Frontend Developer in Berlin with experience in React and Next.js."
   
   ### 2. AI-Powered Boolean Search Generation
   
   The input is passed to OpenAI's GPT-4O-MINI model via LangChain integration, which creates two crucial outputs:
   - A Boolean search string specifically crafted for Google searches targeting LinkedIn profiles
   - A suggested name for the output sheet
   
   - Node: `Generate a Boolean Search String`
   
   Example Output:  
   ```
   site:linkedin.com/in ("Senior Frontend Developer" OR "Lead Frontend Engineer") AND (React OR "Next.js") AND Berlin
   ```
   
   ### 3. Creating and Configuring Google Sheets
   
   A new Google Spreadsheet is created dynamically using the sheet name generated by OpenAI.
   
   - Node: `Create a new sheet`
   - Node: `Columns to add`
   - Node: `Add columns to new sheet`
   
   This spreadsheet will be populated with LinkedIn profile data.
   
   ### 4. Pagination Setup and Initiating Google Search Loop
   
   To simulate navigating through multiple Google search pages, the workflow initializes a `start` parameter at 0 and increases it by 10 per loop iteration — aligning with Google's pagination.
   
   - Node: `set page number for google search`
   - Node: `Adds 10 to start - Go to next page`
   
   ### 5. Authenticated Google Search
   
   To avoid CAPTCHA and improve results accuracy, TopSourcer uses a browser-authenticated session through a header-based cookie string. Users are instructed to use a browser plugin like Cookie-Editor to copy their session cookie and paste it into the workflow.
   
   - URL Called: `https://www.google.com/search?q=...`
   - Node: `Google Boolean Search`
   
   **Important**: The cookie enables Google search access as an authenticated user, bypassing many limitations.
   
   ### 6. Extracting LinkedIn Profile URLs
   
   Once the HTML is returned, the workflow employs smart JavaScript logic to find valid LinkedIn URLs.
   
   - Node: `Extracts all linkedin urls from the google http response`
   
   This JavaScript method uses multiple patterns to find profile links from various HTML structures and formatting inconsistencies.
   
   ### 7. Output to Google Sheets
   
   The clean LinkedIn profile URLs are then appended into your structured Google Sheet.
   
   - Node: `Appends the results to the sheet`
   
   This includes columns for `linkedin_url`, and is later expandable to include inferred metadata like name, headline, skills, and more.
   
   ### 8. Rate Limiting and Looping
   
   To avoid being flagged by Google, the workflow waits 5 seconds between requests.
   
   - Node: `Wait`
   
   If the desired number of results (default: 50) is not yet reached, the loop continues. Otherwise, the workflow stops or can optionally proceed with further enrichment.
   
   ---
   
   ## Third-Party APIs and Services Used
   
   - **OpenAI API**
     - Used to interpret job descriptions and generate Boolean search strings.
   - **Google Sheets API**
     - For dynamically creating spreadsheets and appending rows of extracted data.
   - **Google Search (via HTTP Request + header-based authentication)**
     - To run Boolean-based site-specific searches across Google and target LinkedIn profiles.
   - **Cookie-Editor Chrome Extension**
     - Advised for exporting logged-in session cookies to authenticate Google searches, technically not an API but required for seamless functioning.
   
   ---
   
   ## Why It Matters
   
   TopSourcer is a real-world application of AI and automation that solves a high-friction problem in recruitment. By combining natural language understanding, modern Boolean search logic, authenticated scraping, and structured data output — all orchestrated inside a powerful no-code/low-code platform like n8n — it offers scalable value with minimal manual work.
   
   Whether you’re a recruiter trying to unearth hidden talent or a data professional prototyping HR tools, TopSourcer gives you a framework that’s robust, extendable, and remarkably efficient.
   
   ---
   
   Unlock a new era of talent sourcing — try the TopSourcer workflow. All you need is your OpenAI API key, a Google account, and about 15 minutes to deploy it through n8n.
   
   Let the automation find candidates for you, so you can focus on conversations, not queries.

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.