Step 2: Connect Phantombuster for Post Scraping

Configure the two HTTP nodes that launch and fetch the LinkedIn post data from Phantombuster.

1. In Launch Post Scraper, set URL to https://api.phantombuster.com/api/v2/agent/launch and Method to POST.
2. Set JSON Body to the exact value:
   {
"id": "[YOUR_ID]",
"arguments": {
"profileUrls": [
"https://www.linkedin.com/in/USERNAME/"
],
"numberOfPosts": 1
},
"save": false
}
3. Enable Send Headers and add header X-Phantombuster-Key-1 with value [CONFIGURE_YOUR_API_KEY].
4. In Retrieve Scrape Output, set URL to https://api.phantombuster.com/api/v2/agent/fetch-output and enable Send Query and Send Headers.
5. Add query parameter id with value [YOUR_ID], and set header X-Phantombuster-Key-1 to [CONFIGURE_YOUR_API_KEY].
6. Connect Launch Post Scraper to Retrieve Scrape Output.

Step 3: Set Up AI Comment Generation

Generate a concise, personalized LinkedIn comment using the agent and OpenAI model.

1. In Generate Comment Agent, set Prompt Type to define.
2. Set the Text field to the exact prompt value starting with =You are a professional LinkedIn marketer... and including the expressions like {{ $json.authorName }} and {{ $json.text }}.
3. Connect AI Comment Model as the language model for Generate Comment Agent.
4. Credential Required: Connect your openAiApi credentials in AI Comment Model. This model powers Generate Comment Agent, so add credentials to the model node, not the agent.
5. Connect Retrieve Scrape Output to Generate Comment Agent.

Step 4: Configure Engagement Actions and Logging

Like the post, publish the AI comment, and log the activity in Google Sheets.

1. In Send Post Like, set JSON Body to ={ "id": "[YOUR_ID]", "arguments": { "postUrls": [ {{ $('Retrieve Scrape Output').item.json.postUrl }} ] }, "save": false } and add header X-Phantombuster-Key-1 with [CONFIGURE_YOUR_API_KEY].
2. In Publish Post Comment, set JSON Body to ={ "id": "[YOUR_ID]", "arguments": { "postUrls": [ {{ $('Retrieve Scrape Output').item.json.postUrl }} ], "comments": [ {{ $json.output }} ] }, "save": false } and add header X-Phantombuster-Key-1 with [CONFIGURE_YOUR_API_KEY].
3. Generate Comment Agent outputs to both Send Post Like and Publish Post Comment in parallel.
4. In Record Activity Sheet, set Operation to append, Sheet Name to gid=0, and Document ID to [YOUR_ID].
5. Map columns exactly: Comment to {{ $('Generate Comment Agent').item.json.output }}, PostUrl to {{ $('Retrieve Scrape Output').item.json.postUrl }}, Post text to {{ $('Retrieve Scrape Output').item.json.text }}, Timestamp to {{ $('Retrieve Scrape Output').item.json.timestamp }}, AuthorName to {{ $('Retrieve Scrape Output').item.json.authorName }}, and AuthorProfile to {{ $('Retrieve Scrape Output').item.json.authorProfile }}.
6. Credential Required: Connect your googleSheetsOAuth2Api credentials in Record Activity Sheet.
7. Connect both Send Post Like and Publish Post Comment to Record Activity Sheet.

Step 5: Test and Activate Your Workflow

Verify the scrape, comment generation, and logging pipeline end to end before going live.

1. Click Execute Workflow to run from Scheduled Morning Trigger or test nodes manually in sequence.
2. Confirm Retrieve Scrape Output returns a post with postUrl, authorName, and text.
3. Verify Generate Comment Agent outputs a short comment in output.
4. Check that both Send Post Like and Publish Post Comment succeed and that Record Activity Sheet appends a new row.
5. Toggle the workflow to Active to enable daily execution at 9 AM.