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 job-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/job-scraper)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/job-scraper"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/job-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/job-scraper"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/job-scraper.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 7 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 50 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Data Exfiltration · line 84 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 84 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 103 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 106 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 131 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 103 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00068 | $0.02645 |
| Opus 5 | $0.00034 | $0.01323 |
| Sonnet 5 | $0.00014 | $0.00529 |
| Haiku 4.5 | $0.00007 | $0.00265 |
Grade A, and why
job-scraper scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -X POST "https://api.apify.com/v2/acts/automation-lab~linkedin-jobs-scraper/runs?token=$APIFY_API_TOKEN" \ How it starts
The opening of the file, as written. The whole thing — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Job Scraper
Search for job postings across LinkedIn and Indeed using Apify. Find open roles by keyword, location, company, or job type. Use for hiring signal detection, GTM research, or competitive intelligence.
No LinkedIn cookies. No Indeed login. Just search queries in, structured job data out.
When to Auto-Load
Load this skill when:
- User says "find jobs", "who is hiring", "what roles is [company] hiring for"
- User wants hiring signals ("find companies growing their AI team")
- User wants competitive intelligence ("what is [competitor] hiring for")
- User says "job search", "open roles", "job listings", "job postings"
Prerequisites
Apify API Token
Required for both LinkedIn and Indeed scraping. Set in .env:
APIFY_API_TOKEN=your_token_here
No LinkedIn cookies, Indeed login, or any platform credentials needed. That's the only setup.
Sources
This skill searches two job platforms via Apify actors:
| Source | Apify Actor | Best For | Cost |
|---|---|---|---|
automation-lab/linkedin-jobs-scraper |
B2B, tech, SaaS, enterprise roles. Has seniority level, job function, industries. | ~$0.002/job | |
| Indeed | borderline/indeed-scraper |
Broadest coverage. Richest data — salary, company details, ratings, contacts, street addresses. | ~$0.004/job |
Source Selection Logic
Do NOT ask the user which source to use unless genuinely ambiguous. Decide based on context:
- User specifies a source → use that source only.
- Context strongly suggests one source:
- B2B/tech/SaaS roles, enterprise companies, seniority-level filtering → LinkedIn
- Hourly/blue-collar roles, local/retail jobs, salary-focused search → Indeed
- Company hiring research ("what is Stripe hiring for") → LinkedIn (better company filtering)
- No clear signal → search both sources, deduplicate results by job title + company name, present combined results.
After deciding, tell the user which source(s) you're searching and why. Don't ask — inform.
What ships with it
1 file 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.
- 9d ago First seen · 270 lines · 68 tokens per session scan A 87c6148d08c7
job-scraper is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 68 tokens to every session and 2,645 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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