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 | $0.00055 | $0.02926 |
| Opus 5.5 | $0.00022 | $0.01170 |
| Sonnet 5.5 | $0.00011 | $0.00585 |
| Haiku 4.5 | $0.00006 | $0.00293 |
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 2d 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 — 275 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 the GooseWorks coworker's people-search tools (Fiber, Crustdata, PDL) with a layered fallback, so you only pay for the next source when the last one came up short.
Where this runs
This skill runs only inside the GooseWorks coworker (the coworker in the GooseWorks app). The people-search tools it uses exist only there. They are not on the GooseWorks server that Claude, ChatGPT and other outside agents connect to.
If fiber_person_search, crustdata_person_search and pdl_person_search are not in your tool list, you are outside the coworker. Tell the user that this contact search runs only inside the GooseWorks coworker, and stop. Do not try other tools in their place.
Spend rule
Every search in this skill is paid. Before each paid search or page, tell the customer what it costs and wait for their yes.
- Take the price from the tool's own description, for the page size you are about to ask for. Do not quote a price from memory or from this file.
- Ask again before every next page or next source. A yes covers one search, not the whole fallback chain.
- If they say no, stop and show what you have so far.
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
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.
- 2d ago Changed · -24 lines · -1 tokens per session a433ff998b5c
- 1mo 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 (1,271 stars, last pushed yesterday), licensed MIT. It adds 55 tokens to every session and 2,926 once invoked, about $0.0002 per session on Opus 5.5. 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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