Competitor Post Engagers

What it does

When your agent uses it

• Someone wants to find leads engaging with competitor content
• Scrape people who interact with [company]s LinkedIn posts

Example prompts

• “find leads engaging with competitor content”
• “scrape people who interact with [company]”
• “/competitor-post-engagers”

Requirements

• Python 3
• A credential in APIFY_API_TOKEN
• A credential in APOLLO_API_KEY

Workflow steps

4 steps, taken from the step headings in SKILL.md.

1. 1Intake
2. 2Run the Pipeline
3. 3Review & Refine
4. 4Output

What it can do on your machine

Read from SKILL.md and the folder at commit 4bbe1ef. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Ships 1 file in scripts/ (Python), which the agent can run.

  Shell commands in SKILL.md call:

  • python3

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Hosts in commands or code, which the agent is likely to contact:

  • linkedin.com

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names these keys or tokens, usually read from environment variables:

  • APIFY_API_TOKEN
  • APOLLO_API_KEY

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Competitor Post Engagers loads about 1.8k tokens when it runs. Until then it costs about 101 tokens; SKILL.md has 708 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~101

When it runs · the whole SKILL.md, loaded when a task matches

~1.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

• NoteMentions a .env fileSKILL.md:143

  I token** — set as `APIFY_API_TOKEN` in `.env`

• NoteMentions a .env fileSKILL.md:144

  API key** — set as `APOLLO_API_KEY` in `.env` (for company enrichment)

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from gooseworks-ai/goose-skills at commit 4bbe1ef, republished under its MIT licence (© gooseworks-ai). 708 words, ~1,825 tokens.

name

competitor-post-engagers

description

Find leads by scraping engagers from a competitor's top LinkedIn posts. Given one or more company page URLs, scrapes recent posts, ranks by engagement, selects the top N, extracts all reactors and commenters, ICP-classifies, and exports CSV. Use when someone wants to "find leads engaging with competitor content" or "scrape people who interact with [company]'s LinkedIn posts".

tags

lead-generation

competitor-post-engagers-config.json

{
  "name": "<run-name>",
  "company_urls": ["https://www.linkedin.com/company/<competitor>/"],
  "days_back": 30,
  "max_posts": 50,
  "max_reactions": 500,
  "max_comments": 200,
  "top_n_posts": 1,
  "icp_keywords": ["sales", "revenue", "growth", "SDR", "BDR", "outbound"],
  "exclude_keywords": ["software engineer", "developer", "designer"],
  "enrich_companies": true,
  "competitor_company_names": ["<competitor-name>"],
  "industry_keywords": ["freight", "logistics", "trucking", "transportation", "3pl", "supply chain", "carrier", "brokerage", "shipping", "warehousing"],
  "output_dir": "output"
}

python3 skills/competitor-post-engagers/scripts/competitor_post_engagers.py \
  --config competitor-post-engagers-config.json \
  [--test] [--yes] [--skip-company-enrich] [--top-n 3] [--max-runs 30]

python3 skills/competitor-post-engagers/scripts/competitor_post_engagers.py \
  --config competitor-post-engagers-config.json --test --yes

python3 skills/competitor-post-engagers/scripts/competitor_post_engagers.py \
  --config competitor-post-engagers-config.json --yes

© gooseworks-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (scripts) in skills/lead-generation/capabilities/competitor-post-engagers of gooseworks-ai/goose-skills.

• SKILL.md
• scripts/competitor_post_engagers.py
• skill.meta.json

Open the folder on GitHubat commit 4bbe1ef

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in gooseworks-ai/goose-skills, which our catalogue first saw on October 7, 2026.

• criptogus/agent-evolve-network.claude/skills/competitor-post-engagers