Goose Skills is a library of workflows and data APIs that lets coding agents handle growth and go-to-market work such as advertising, social media, content, SEO, lead generation, and customer research. It is intended for teams using Claude Code, Cursor, Codex, and similar agents. The catalogue entries are its reusable skills.
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 gooseworks-ai/goose-skills --skill meta-ad-scrapergit clone --depth 1 https://github.com/gooseworks-ai/goose-skillsWrote 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/gooseworks-ai/goose-skills/meta-ad-scraper)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/meta-ad-scraper"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/meta-ad-scraper/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/gooseworks-ai/goose-skills/meta-ad-scraper"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/meta-ad-scraper.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 | $0.00067 | $0.01254 |
| Opus 5 | $0.00034 | $0.00627 |
| Sonnet 5 | $0.00013 | $0.00251 |
| Haiku 4.5 | $0.00007 | $0.00125 |
Grade A, and why
meta-ad-scraper 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 13d 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.
How it starts
The opening of the file, as written. The whole thing — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meta Ad Library Scraper
Scrape ads from Meta's Ad Library using the Apify apify/facebook-ads-scraper actor. Covers Facebook, Instagram, Messenger, Threads, and WhatsApp.
Quick Start
Requires APIFY_API_TOKEN env var (or --token flag). Install dependency: pip install requests.
# Search ads by company name
python3 skills/meta-ad-scraper/scripts/search_meta_ads.py \
--company "Nike"
# Search with country filter
python3 skills/meta-ad-scraper/scripts/search_meta_ads.py \
--company "Shopify" --country US
# Search by keyword (broader than company name)
python3 skills/meta-ad-scraper/scripts/search_meta_ads.py \
--company "project management software"
# Limit results
python3 skills/meta-ad-scraper/scripts/search_meta_ads.py \
--company "HubSpot" --max-ads 20
# Search by Facebook Page URL directly
python3 skills/meta-ad-scraper/scripts/search_meta_ads.py \
--page-url "https://www.facebook.com/nike"
# Only active ads (default), or all ads
python3 skills/meta-ad-scraper/scripts/search_meta_ads.py \
--company "Salesforce" --ad-status all
# Human-readable summary
python3 skills/meta-ad-scraper/scripts/search_meta_ads.py \
--company "Stripe" --output summary
How It Works
- Takes a company name, keyword, or Facebook Page URL
- Constructs a Meta Ad Library URL with the search query and filters
- Calls the Apify
apify/facebook-ads-scraperactor via REST API - Polls until the run completes, then fetches the dataset
- Parses and outputs ad data as JSON or human-readable summary
Resolving Company Name → Ads
The script handles the advertiser lookup automatically:
- Company name: Constructs a search URL like
facebook.com/ads/library/?q=CompanyName— the Apify actor searches Meta's Ad Library for matching advertisers - Page URL: If you have the Facebook Page URL, pass it via
--page-urlfor exact matching - Domain: You can also pass a domain and the script will search for it
No need to manually find Page IDs. The Apify actor resolves the search internally.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 13d ago First seen · 137 lines · 67 tokens per session scan A b484c3fe20f0
meta-ad-scraper is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 67 tokens to every session and 1,254 once invoked, about $0.0003 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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