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 hiring-signal-outreachgit 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/hiring-signal-outreach)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/hiring-signal-outreach"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/hiring-signal-outreach/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/hiring-signal-outreach"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/hiring-signal-outreach.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 | $0.00078 | $0.04957 |
| Opus 5 | $0.00039 | $0.02478 |
| Sonnet 5 | $0.00016 | $0.00991 |
| Haiku 4.5 | $0.00008 | $0.00496 |
Grade A, and why
hiring-signal-outreach 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 — 534 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hiring Signal Outreach
Detects job postings at target companies where the role being hired for is one your product augments, replaces, or directly supports. Finds the right people to contact (not just the person being hired — the hiring manager, budget holder, and potential champions), then drafts personalized outreach using the job posting as the hook.
Why hiring signals work: When a company posts a job, they've already acknowledged the problem your product solves. They've budgeted for it (headcount is budget). They're actively evaluating how to solve it. Your email arrives at exactly the moment they're thinking about this problem — and you're offering a faster, cheaper, or complementary solution.
When to Auto-Load
Load this composite when:
- User says "check if any of these companies are hiring for roles we replace", "job posting signals", "hiring signal outreach"
- User has a list of companies and wants to find those hiring for relevant roles
- An upstream workflow (TAM Pulse, company monitoring) triggers a hiring signal check
Step 0: Configuration (One-Time Setup)
On first run for a client/user, collect and store these preferences. Skip on subsequent runs.
Role Mapping (Critical — This Defines What Signals Matter)
| Question | Purpose | Stored As |
|---|---|---|
| What does your product do? (1-2 sentences) | Match against job descriptions | company_description |
| What job roles does your product replace? | Strongest signal — they're hiring for what you automate | roles_replaced |
| What job roles does your product augment? | Good signal — your product makes this person more effective | roles_augmented |
| What job roles buy your product? | Contact finding — who holds the budget | buyer_titles |
| What job roles champion your product? | Contact finding — who feels the pain daily | champion_titles |
| What job roles use your product? | Contact finding — who would operate it | user_titles |
| What keywords in a job description indicate relevance? | Filters out false positives | jd_keywords |
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 · 534 lines · 78 tokens per session scan A 4c90df748c85
hiring-signal-outreach is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 78 tokens to every session and 4,957 once invoked, about $0.0004 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.
Other skills, from other repositories
sequence-architect
Design a 4-6 touch outreach cadence with channels, timing, tonal arc, and branching. Use when starting a new sequence from scratch given an ICP and offer.
icebreaker
Draft 3 distinct opening messages for a specific prospect, anchored on a why-now and a why-this-person. Use when sending a high-leverage first touch where personalization is worth the time.
sequence-doctor
Audit an outreach sequence and produce a ranked fix list. Use when reply rates are low, when you want a second opinion before sending, or when rewriting a sequence from scratch.
jargon-bingo
Score sales calls, emails, or posts on a 5x5 bingo card of cliches. Mostly for fun; quietly useful for spotting jargon-heavy patterns.
prospect-twin
Build a believable persona simulation of a prospect from their LinkedIn profile, then practice outreach against them. Use when preparing for a high-stakes outreach or call, when iterating on openers, or when testing whether a pitch lands.
cringe-translator
Translate sales-jargon-laden LinkedIn messages into what the sender actually means. Mostly for fun; occasionally educational about why a message tanked.