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 google-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/google-ad-scraper)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/google-ad-scraper"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/google-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/google-ad-scraper"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/google-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 | $0.00035 | $0.01016 |
| Opus 5 | $0.00017 | $0.00508 |
| Sonnet 5 | $0.00007 | $0.00203 |
| Haiku 4.5 | $0.00003 | $0.00102 |
Grade A, and why
google-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 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.
How it starts
The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Google Ads Scraper
Scrape ads from Google Ads using the Apify burbn/google-ads-search actor. Search by domain to get ad creatives, formats, and campaign details.
Quick Start
Requires APIFY_API_TOKEN env var (or --token flag).
# Search by domain (recommended)
python3 skills/google-ad-scraper/scripts/search_google_ads.py \
--domain "hubspot.com"
# Search by company name (resolves to domain via transparency center)
python3 skills/google-ad-scraper/scripts/search_google_ads.py \
--company "Nike"
# Limit results
python3 skills/google-ad-scraper/scripts/search_google_ads.py \
--domain "hubspot.com" --max-ads 30
# Human-readable summary
python3 skills/google-ad-scraper/scripts/search_google_ads.py \
--domain "stripe.com" --output summary
How It Works
- Domain Input: Pass the target company's domain directly via
--domain - Company Name Resolution (optional): If only
--companyis provided, the script searches Google Ads Transparency Center using Apify's web-scraper (Puppeteer) to resolve the company name to advertiser info - Ad Scraping: Calls the Apify
burbn/google-ads-searchactor with{"domain": "...", "maxItems": N} - Output: Returns ads as JSON or human-readable summary
CLI Reference
| Flag | Default | Description |
|---|---|---|
--domain |
none | Company domain (e.g. hubspot.com) — recommended |
--company |
none | Company name (resolved to domain via transparency center) |
--max-ads |
50 | Maximum number of ads to return |
--output |
json | Output format: json or summary |
--token |
env var | Apify token (prefer APIFY_API_TOKEN env var) |
--timeout |
300 | Max seconds to wait for Apify run |
At least one of --company or --domain is required.
Output Fields
Each ad in the output contains:
{
"advertiserId": "AR13129532367502835713",
"advertiserName": "Nike, Inc.",
"creativeId": "CR12345678901234567890",
"originalUrl": "https://www.nike.com/",
"imageUrl": "https://...",
"variantFormat": "TEXT",
"variantContent": "Shop the latest Nike shoes...",
"variants": [...],
"variantCount": 3,
"startDate": "2026-01-15"
}
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.
- 12d ago First seen · 115 lines · 35 tokens per session scan A bf4862bef8e9
google-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 35 tokens to every session and 1,016 once invoked, about $0.0002 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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