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Manus
Grok+17 agentsweft linkedin commenter discovery
Extract and rank relevant prospects from LinkedIn post comments with verified evidence and profile links.
Free
weft linkedin commenter discovery
Example session with this skill installed
Find people worth contacting from this LinkedIn discussion: https://www.linkedin.com/posts/example-post-123. I am looking for CTOs and Engineering Managers interested in LLM observability.
- Read your context and instructions
- Compiled the weft linkedin commenter
- Generated the data export
I have analyzed the LinkedIn post and screened 84 root comments. Based on your interest in LLM observability, I have identified 5 high-relevance prospects.
LinkedIn Prospect Research Brief
| Name | Role / source headline | Company | LinkedIn profile | Comment evidence | Why relevant |
|---|---|---|---|---|---|
| Sarah Chen | CTO & Co-founder | ObservaAI | profile | "We've been struggling with trace latency in RAG flows..." | Direct match: CTO at an AI company discussing observability pain points. |
| Marcus Thorne | Head of Engineering | DataScale | profile | "How does this approach handle cost-tracking at the prompt level?" | Engineering leadership role asking specific technical questions about LLM costs. |
| Elena Rodriguez | VP of Engineering | CloudNative | profile | "Monitoring non-deterministic outputs is the next big hurdle for us." | Engineering manager explicitly identifying a need for observability solutions. |
| David Wu | Lead Architect | FinTech OS | profile | "Evaluation loops are still too manual in our current stack." | Technical decision-maker looking for automation in the LLM lifecycle. |
| Jamie Vora | Technical Director | AI Core | profile | "Does your SDK support OpenTelemetry for LLM spans?" | Technical leader verifying integration capabilities for observability. |
Coverage Details:
- Comments examined: 84
- Exclusions: 12 (Spam/Bot), 4 (Company Accounts)
- Shortlist size: 5
Next steps
- Review the specific comment evidence to personalize your outreach.
- Visit the LinkedIn profiles to verify current employment status.
- Save this table as a CSV for import into your CRM or lead tracker.
Receipt
| Service / action | Paid USD | Held USD | Payment status | Result |
|---|---|---|---|---|
| Apify / Prepaid Credit | 1.00 | 0.00 | Success | Token Issued |
| Actor / post-comments | 0.00 | 0.01 | Pending | Data Returned |
weft-linkedin-commenter-discovery.csv
CSV · data export
Example file from a real run - the skill writes it into your workspace.
Connects securely to your tools. The creator never sees your data.
About this skill
The problem
Finding potential leads or partners in LinkedIn comment sections is manual and time-consuming. Developers and sales teams waste hours clicking through profiles and copy-pasting data to identify who is actually worth contacting.
What it does
- Identifies and deduplicates commenters from a specific LinkedIn post URL.
- Extracts roles, headlines, and company information from profile data.
- Pairs every entry with the specific comment text that triggered their inclusion.
- Ranks prospects based on relevance to your specific target criteria or industry interest.
- Provides a structured research brief with direct LinkedIn profile links and evidence.
Frameworks & tools
This skill utilizes the weft protocol for secure payments and credential management, and Apify for data extraction.
Why this beats prompting it yourself
Standard LLM prompts cannot access live LinkedIn comment data behind auth walls or handle large-scale data extraction. This skill integrates secure paid access via Weft to pull real-time data, merges duplicate entries, and filters out noise like company accounts and spam that would otherwise clutter your context window.
Use cases
- Identify high-intent prospects from a competitor's viral announcement post.
- Find relevant industry experts contributing to a specific technical discussion.
- Build a shortlist of potential hires commenting on a job-related thread.
Known limitations
Limited to root comments only (replies are skipped). Does not extract email addresses or automate outreach. Requires a LinkedIn post URL; cannot search for posts by keyword.
How to install
Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.
- 1
Download the ZIP
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- 2
Unzip into your skills folder
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- 3
Ask your agent to use it
Restart the agent if it was already running. It picks the skill up automatically - no config needed.
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