What is competitor-engagers?

A lead-listing tool that finds people who comment on or react to competitors' LinkedIn posts. LinkedIn is a professional social network, and these actions show that someone has engaged with a competitor's content.

Use it to discover prospects for outreach from a supplied company website and its competitors. It collects company and employee posts, deduplicates the commenters and reactors, and saves them in a CSV file.

It removes the need to manually inspect competitor posts and collect potential contacts. The results still need filtering because engagement does not prove that someone is a suitable customer.

competitor-engagers — Skill for Claude Code by AlexisMarasigan

Install

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.

Any agent

npx skills add AlexisMarasigan/coldoutboundskills --skill competitor-engagers

Clone the repo

git clone --depth 1 https://github.com/AlexisMarasigan/coldoutboundskills

Made for: Claude Code.

Or install coldoutboundskills, the plugin that ships this one along with the rest of its 28 skills.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/alexismarasigan/coldoutboundskills/competitor-engagers/github.svg)](https://agentmods.dev/skills/alexismarasigan/coldoutboundskills/competitor-engagers)

Your own site

<a href="https://agentmods.dev/skills/alexismarasigan/coldoutboundskills/competitor-engagers"><img src="https://agentmods.dev/badge/skills/alexismarasigan/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/alexismarasigan/coldoutboundskills/competitor-engagers"><img src="https://agentmods.dev/badge/skills/alexismarasigan/coldoutboundskills/competitor-engagers.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 75 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,071 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin 100% copy Near-identical to another mod in the catalogue.

Token cost

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 5.5	$0.00030	$0.00428
Sonnet 5.5	$0.00015	$0.00214
Haiku 4.5	$0.00007	$0.00107

Measured 2mo ago against content hash bf9ed8c002ef, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 2mo 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.

Origin

This is a copy

100% identical to competitor-engagers — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/competitor-engagers/SKILL.md · 104 lines

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-auth
```
If 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
```

Read the full file on GitHub · 104 lines

Changes

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.

2mo ago First seen · 104 lines · 75 tokens per session scan A bf9ed8c002ef

Subscribe to this mod's changes

competitor-engagers is a skill published in the GitHub repository AlexisMarasigan/coldoutboundskills (5 stars, last pushed 6mo ago), licensed MIT. It adds 75 tokens to every session and 1,071 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to competitor-engagers, differing in 2 lines, and is treated as a copy.

Marketing and SEO

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