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-posting-intentgit 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-posting-intent)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/job-posting-intent"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/job-posting-intent/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-posting-intent"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/job-posting-intent.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 | $0.00068 | $0.02106 |
| Opus 5 | $0.00034 | $0.01053 |
| Sonnet 5 | $0.00014 | $0.00421 |
| Haiku 4.5 | $0.00007 | $0.00211 |
Grade A, and why
job-posting-intent 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 — 241 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Job Posting Intent Detection
Find companies that are hiring for roles related to the problem you solve. A job posting is a budget signal — the company has allocated money to solve a problem your product addresses.
Results are automatically exported to a Google Sheet with signal strength, decision-maker suggestions, outreach angles, and personalization context.
Why This Works
When a company posts a job, they've:
- Allocated budget (headcount is expensive)
- Acknowledged the problem exists
- Started actively solving it
If your product helps solve that problem faster, cheaper, or better than a hire alone, the timing is perfect.
Cost
Apify Actor: harvestapi/linkedin-job-search (pay-per-event)
| Component | Cost |
|---|---|
| Actor start (per run) | $0.001 |
| Per job result | $0.001 |
| Apify platform fee | +20% |
Typical run costs:
| Scenario | Titles | Jobs/title | Runs | Est. Cost |
|---|---|---|---|---|
| Quick scan | 3 | 25 | 3 | ~$0.09 |
| Standard | 5 | 25 | 5 | ~$0.16 |
| Deep search | 5 | 100 | 5 | ~$0.60 |
| Multi-location | 5×3 | 25 | 15 | ~$0.47 |
Google Sheet creation is free (uses Rube/Composio integration).
Always run --estimate-only first to see the Apify cost before executing.
Track usage: https://console.apify.com/billing
Setup
1. Apify API Token
# Get your token at https://console.apify.com/account/integrations
export APIFY_API_TOKEN="apify_api_YOUR_TOKEN_HERE"
2. Install dependencies
pip3 install requests
3. Rube/Composio (for Google Sheets)
Google Sheet creation uses Rube MCP with Composio. The token is preconfigured.
If it stops working, update the RUBE_TOKEN env var or the default in search_jobs.py.
Usage
Step 1: Define your ICP and target titles
Think about it this way: "If a company is hiring for [role], it means they're investing in [problem area you solve]."
Examples:
- GTM agency: "Growth Marketing Manager", "SDR Manager", "RevOps Engineer", "GTM Engineer"
- AI dev tools: "AI Engineer", "ML Ops Engineer", "Prompt Engineer", "LLM Engineer"
- Sales automation: "SDR", "BDR Manager", "Sales Ops", "Revenue Operations"
What ships with it
4 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.
- 9d ago First seen · 241 lines · 68 tokens per session scan A 3669bb49c0af
job-posting-intent 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 2,106 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.
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.