Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add growthenginenowoslawski/coldoutboundskills --skill competitor-engagersgit clone --depth 1 https://github.com/growthenginenowoslawski/coldoutboundskillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/growthenginenowoslawski/coldoutboundskills/competitor-engagers)<a href="https://agentmods.dev/skills/growthenginenowoslawski/coldoutboundskills/competitor-engagers"><img src="https://agentmods.dev/badge/skills/growthenginenowoslawski/coldoutboundskills/competitor-engagers/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/growthenginenowoslawski/coldoutboundskills/competitor-engagers"><img src="https://agentmods.dev/badge/skills/growthenginenowoslawski/coldoutboundskills/competitor-engagers.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00075 | $0.01071 |
| Opus 5 | $0.00037 | $0.00535 |
| Sonnet 5 | $0.00015 | $0.00214 |
| Haiku 4.5 | $0.00007 | $0.00107 |
Grade A, and why
competitor-engagers scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- competitor-engagers — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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=<your key from https://rapidapi.com/apibuilderz/api/realtime-linkedin-bulk-data>
OPENROUTER_API_KEY=<your key from https://openrouter.ai/keys>
Test your credentials:
npm run competitor-engagers -- --check-auth
Steps
-
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.
-
Run the auth preflight check:
npm run competitor-engagers -- --check-authIf it fails, help the user set up their API keys.
-
Run the main script:
npm run competitor-engagers -- --url={domain} --competitors={count} --posts={postsPerCompany} {--extra-competitor=URL ...} --verbose -
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:npm run competitor-engagers -- --url={domain} --resume
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 104 lines · 75 tokens per session scan A bf9ed8c002ef
competitor-engagers is a skill published in the GitHub repository growthenginenowoslawski/coldoutboundskills (702 stars, last pushed 24d ago), licensed MIT. It adds 75 tokens to every session and 1,071 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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