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 company-contact-findergit 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/company-contact-finder)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/company-contact-finder"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/company-contact-finder/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/company-contact-finder"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/company-contact-finder.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 | $0.00056 | $0.02749 |
| Opus 5 | $0.00028 | $0.01375 |
| Sonnet 5 | $0.00011 | $0.00550 |
| Haiku 4.5 | $0.00006 | $0.00275 |
Grade A, and why
company-contact-finder 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 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.
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 — 299 lines — stays where its author put it; the contents beside it link to each section on GitHub.
company-contact-finder
Find decision-makers at a specific company by name and target titles. Uses Gooseworks MCP tools (Apollo, Crustdata, Fiber, PDL) with a layered fallback strategy to maximize results while minimizing cost.
Inputs
| Input | Required | Default | Description |
|---|---|---|---|
| company_name | Yes | -- | The company to search (e.g., "EisnerAmper") |
| company_linkedin_url | No | -- | Company LinkedIn URL for disambiguation |
| target_titles | Yes | -- | List of titles to find (e.g., ["Partner", "Controller", "VP Finance"]) |
| num_results | No | 10 | How many contacts to return |
Procedure
Step 1: Understand the Request
Parse the user's request to extract:
- company_name (required) -- the company to search at
- company_linkedin_url (optional) -- helps disambiguate common names
- target_titles (required) -- list of job titles or roles to find (e.g., ["Partner", "Controller", "VP Finance", "CFO"])
- num_results (optional, default 10) -- how many contacts to return
If the user does not provide target titles, ask for them. Suggest common senior titles based on context:
- For accounting/CPA firms: Partner, Managing Director, Controller, CFO, VP Finance
- For tech companies: VP Engineering, CTO, Head of Product, Director of Engineering
- For general B2B: VP, Director, C-Level, Head of
Step 2: Apollo Search (Primary — cheapest at $0.01/call)
Apollo is the cheapest search provider. Start here for all searches.
Call:
apollo_person_search(
person_titles: ["Partner", "Controller", "VP Finance"],
organization_domains: ["eisneramper.com"],
per_page: 25
)
If you don't have the company domain, use q_keywords with the company name:
apollo_person_search(
person_titles: ["Partner", "Controller", "VP Finance"],
q_keywords: "EisnerAmper",
per_page: 25
)
Parse the response: Each result contains: name, title, company, LinkedIn URL, location, email, and other profile fields. Extract and collect all results into a working list.
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 · 299 lines · 56 tokens per session scan A b8061e59775c
company-contact-finder is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 56 tokens to every session and 2,749 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 2026-09-03.
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