Competitor Engagers

Competitor Engagers

Finds people who are actively engaging with your competitors on LinkedIn — the highest-intent prospects for cold outreach.

Required step: Qualify with /icp-prompt-builder (do not skip)

After collecting the engager CSV, sample ~50 rows and run /icp-prompt-builder before scaling further. LinkedIn engagement alone doesn't guarantee ICP fit — someone who reacted to a competitor's post might be a peer, a candidate, a student, or an actual buyer. Qualifying filters separates them.

Why required: unfiltered engager lists typically have 30-50% non-ICP rows (fans, peers, recruiters, students). Running /icp-prompt-builder on a 50-row sample, tuning the qualification prompt, then applying it to the full list cuts wasted enrichment + send costs. Takes 10-15 min.

Setup (First Time Only)

Before running, ensure these environment variables are set in ~/.env:

RAPIDAPI_KEY=
OPENROUTER_API_KEY=

Test your credentials:

npm run competitor-engagers -- --check-auth

Steps

1. Parse the user's input. They must provide a website URL (e.g., "clay.com"). Ask for:

• How many competitors to discover (default: 20)
• Posts per company (default: 30)
• Any specific competitor LinkedIn URLs to include

If the user just says "run it" or provides only a URL, use all defaults.

1. Run the auth preflight check:

``bash npm run competitor-engagers -- --check-auth `` If it fails, help the user set up their API keys.

1. Run the main script:

``bash npm run competitor-engagers -- --url={domain} --competitors={count} --posts={postsPerCompany} {--extra-competitor=URL ...} --verbose ``

1. The script prints live progress. It can take 30-120 minutes for a full run (20 competitors x 200 employees x engagement collection). If interrupted, re-run with --resume:

``bash npm run competitor-engagers -- --url={domain} --resume ``

1. Once complete, read the output CSV from ~/output/competitor-engagers/ and present:

• Total unique engagers found
• Top 10 most active engagers (by total_engagements)
• Breakdown by competitor
• Output file path

1. Offer follow-up actions:

• "Want to filter to only people with 3+ engagements?"
• "Want to enrich these with email addresses?"
• "Want to run this for a different company?"
• "Want me to start a dry run first to validate the competitor list?"

CLI Reference

--url=            Target company domain (required)
--competitors=         AI-discovered competitor count (default: 20)
--posts=               Posts per company (default: 30)
--extra-competitor=  Add a competitor manually (repeatable)
--dry-run                 Discover competitors only, skip engagement scraping
--resume                  Resume from checkpoint after interruption
--verbose                 Detailed per-request logging
--check-auth              Test API credentials and exit

Notes

• Skips people employed at the target company OR any of the competitor companies
• Comments and reactions only (reposts not collected)
• 90-day lookback window for posts
• Fetches up to 200 employees per competitor
• One row per person in output (deduplicated, sorted by engagement count)
• Checkpoint saved at ~/output/competitor-engagers/{domain}-checkpoint.json

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What to do next

Run /icp-prompt-builder on a 50-row sample of the engagers CSV (required step — LinkedIn engagement alone doesn't guarantee ICP fit). Then /list-quality-scorecard on the filtered list.

Or wait: if your sample shows heavy non-ICP noise (>50% fans/peers/recruiters), the competitors you chose may be too broad. Re-run this skill with tighter competitor selection.

Related skills

• /icp-prompt-builder — required filter pass on this skill's output
• /list-quality-scorecard — grade the filtered list
• /email-waterfall — if LinkedIn engagement doesn't include emails
• /campaign-copywriting — write copy referencing their specific engagement pattern

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: growthenginenowoslawski
• Source: growthenginenowoslawski/coldoutboundskills
• License: MIT

Install and usage instructions live in the source repository linked above.