with one click
Search for jobs matching your skills, experience, and preferences
npx skills add https://github.com/gooseworks-ai/goose-skills --skill job-searchCopy and paste this command into Claude Code to install the skill
Search for jobs matching your skills, experience, and preferences
npx skills add https://github.com/gooseworks-ai/goose-skills --skill job-searchCopy and paste this command into Claude Code to install the skill
For paid lead-gen and participant-recruitment ads, replaces vanity CPA with true CAC per qualified lead by joining ad-platform data with downstream funnel events, surfaces tracking gaps, and classifies every creative into Scale / Keep / Investigate / Cut.
Pre-flight policy check for Meta ads. Takes ad copy plus advertiser context, resolves and fetches the relevant Meta transparency-center policy pages at runtime, and returns a Pass / Fix Required / Block verdict with cited findings and rewrites.
Diagnose Meta Ads campaign performance using Meta's actual system mechanics — Breakdown Effect, Learning Phase, Auction Overlap, Pacing, and Creative Fatigue — and produce structured, testable recommendations that avoid judging segments by average CPA instead of marginal efficiency.
Create a custom web dashboard (React + Vite + Express) inside your sandbox to visualize the agent's Turso database. The dashboard is served on port 3847 and the user sees it live in the "App" tab in Gooseworks. Use when the user asks for a dashboard, visualization, chart, metric view, or any custom UI powered by their agent's data.
Creates a new graphics format spec (custom canvas dimensions + content rules) and publishes it to the Gooseworks library so any agent can render against it. Use when the existing community formats (carousel, story, infographic, slides, poster, chart, tweet, plus community additions) don't fit the user's canvas — e.g., LinkedIn banner 1584×396, story cover 1080×1920, event flyer 8.5×11in. Mirrors goose-graphics-create-style but for formats.
End-to-end skill that turns a single reference image into a published Gooseworks style — analyzes the image, drafts the slim style spec, renders a hero example plus 2-3 additional formats via Playwright, writes the `gooseworks-style.json` manifest, and publishes via `npx gooseworks styles publish` so other agents can discover it. Mirrors goose-graphics-create-format but for styles.
| name | job-search |
| description | Search for jobs matching your skills, experience, and preferences |
| source | orthogonal |
Read your credentials from ~/.gooseworks/credentials.json:
export GOOSEWORKS_API_KEY=$(python3 -c "import json;print(json.load(open('$HOME/.gooseworks/credentials.json'))['api_key'])")
export GOOSEWORKS_API_BASE=$(python3 -c "import json;print(json.load(open('$HOME/.gooseworks/credentials.json')).get('api_base','https://api.gooseworks.ai'))")
If ~/.gooseworks/credentials.json does not exist, tell the user to run: npx gooseworks login
All endpoints use Bearer auth: -H "Authorization: Bearer $GOOSEWORKS_API_KEY"
Search for jobs matching your skills, experience level, and location preferences.
Use Fiber to search for jobs:
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"fiber","path":"/v1/job-search"}'
"searchParams": {
"job_titles": ["Software Engineer", "Full Stack Developer"],
"locations": ["San Francisco", "Remote"],
"experience_level": "senior"
}
}'
Get company information for interesting roles:
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"fiber","path":"/v1/company-search"}'
"searchParams": {
"company_names": ["Stripe", "Figma", "Notion"]
}
}'
Use Brand.dev for detailed company info:
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"brand-dev","path":"/v1/brand/retrieve","query":{"domain":"stripe.com"}}'
Find people at the company to network with:
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"fiber","path":"/v1/people-search"}'
"searchParams": {
"company_names": ["Stripe"],
"job_titles": ["Engineering Manager", "VP Engineering", "CTO"]
}
}'
Find email for outreach:
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"hunter","path":"/v2/email-finder","query":{"domain":"stripe.com","first_name":"John","last_name":"Doe"}}'
# Search for remote AI jobs
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"fiber","path":"/v1/job-search"}'
"searchParams": {
"job_titles": ["Machine Learning Engineer", "AI Engineer"],
"locations": ["Remote"],
"keywords": ["LLM", "generative AI"]
}
}'
# Research a company
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"fiber","path":"/v1/natural-language-search/companies"}'
"query": "Tell me about Anthropic - funding, team size, culture"
}'
List all endpoints, or add a path for parameter details:
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/search \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"prompt":"brand-dev API endpoints"}' api show fiber
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/search \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"prompt":"hunter API endpoints"}'
Example: `curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/details \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"olostep","path":"/v1/scrapes`"}' for endpoint parameters.