Book restaurant reservations via browser automation. Use when asked to make dinner reservations, book a table, or find availability at restaurants. Supports OpenTable, Resy, and direct restaurant booking sites.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
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"
Book reservations using Notte browser automation via Orthogonal.
npm install -g @orth/cli) or API keycurl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"notte","path":"/sessions/start"}'
--body '{"browser_type":"chromium","headless":true,"solve_captchas":true,"idle_timeout_minutes":10}'
Save the session_id from the response.
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"notte","path":"/sessions/{session_id}/page/execute"}'
--body '{"type":"goto","url":"https://www.opentable.com/r/{restaurant}?datetime=2026-02-17T19:00&covers=2"}'
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"notte","path":"/sessions/{session_id}/page/execute"}'
--body '{"type":"click","selector":"button:has-text(\"7:00 PM\")"}'
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"notte","path":"/sessions/{session_id}/page/execute"}'
--body '{"type":"click","selector":"button:has-text(\"Select\")"}'
# First name
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"notte","path":"/sessions/{session_id}/page/execute"}'
--body '{"type":"fill","selector":"input#firstName","value":"John"}'
# Last name
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"notte","path":"/sessions/{session_id}/page/execute"}'
--body '{"type":"fill","selector":"input#lastName","value":"Doe"}'
# Email
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"notte","path":"/sessions/{session_id}/page/execute"}'
--body '{"type":"fill","selector":"input#email","value":"john@example.com"}'
# Phone
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"notte","path":"/sessions/{session_id}/page/execute"}'
--body '{"type":"fill","selector":"input#phoneNumber","value":"4155551234"}'
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"notte","path":"/sessions/{session_id}/page/execute"}'
--body '{"type":"click","selector":"text=I agree to the restaurant"}'
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"notte","path":"/sessions/{session_id}/page/execute"}'
--body '{"type":"click","selector":"button:has-text(\"Complete reservation\")"}'
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"notte","path":"/sessions/{session_id}/page/scrape"}'
--body '{"only_main_content":true}'
Look for "confirmed" in the response.
# Start session
curl -X POST "https://api.orth.sh/v1/run" \
-H "Content-Type: application/json" \
-d '{
"api": "notte",
"path": "/sessions/start",
"body": {
"browser_type": "chromium",
"headless": true,
"solve_captchas": true,
"idle_timeout_minutes": 10
}
}'
# Execute actions (same pattern)
curl -X POST "https://api.orth.sh/v1/run" \
-H "Content-Type: application/json" \
-d '{
"api": "notte",
"path": "/sessions/{session_id}/page/execute",
"body": {"type":"goto","url":"https://www.opentable.com/..."}
}'
| Field | Selector |
|---|---|
| First name | input#firstName |
| Last name | input#lastName |
input#email | |
| Phone | input#phoneNumber |
| Terms checkbox | text=I agree to the restaurant |
| Submit | button:has-text('Complete reservation') |
| Time slots | button:has-text('7:00 PM') |
| Seating select | button:has-text('Select') |
Search OpenTable and extract from URL:
restref=1906 → Foreign CinemaExample URL format:
https://www.opentable.com/r/{restaurant-slug}?restref={id}&datetime={YYYY-MM-DDTHH:MM}&covers={n}
fill action with value param (not type with text)If restaurant uses Resy:
https://resy.com/cities/{city}/venues/{restaurant}?date={YYYY-MM-DD}&seats={n}
Similar flow but different selectors. Scrape page first to identify form fields.
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Research supported advertising promises from a specific buyer's context, current product facts, customer language and observed ads. Turn them into static, video or copy ideas; match video ideas to actual recipes and save a product-scoped angle bank for write-video-ad-script. Product-led discovery can use verified facts without reviews. Reference persistence and reach are observations, not proof of performance.
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Analyze ad campaign performance data (Google, Meta, LinkedIn) to identify what's working, what's wasting budget, and specific cut/scale/test recommendations. Runs statistical analysis, funnel diagnostics, and multi-channel budget reallocation with specific dollar-amount shift recommendations and scenario modeling.
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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.
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The intake stage of a Meta ad harness. Researches the brand first, states what it assumes, and asks only what it cannot infer and what would change money, claims or legal exposure if guessed wrong — at most four questions a turn, in plain business language. Writes the brand's stable facts (ads/brand.md), the campaign brief, and a log of what was asked vs assumed. Use it when someone wants to run Meta ads and the brand's ad facts are not yet recorded.
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Checks paid ads against the ad platform's rules (Meta, TikTok, Google, LinkedIn and others) and the brand's category rules: the copy, on-image or on-screen text, pictures and people. Rewrites what can be fixed honestly, adds the disclosures that are needed, and flags anything that needs a human or legal review, with one pass, fixed or flag line per ad and platform. Use alone when you already have the ad text or images and know where they will run; otherwise run the playbook for the job (e.g. make-static-ads, make-content, email-lifecycle).
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Analyze the message match between your ads and landing pages. Checks if the promise in the ad copy carries through to the landing page headline, body, and CTA. Flags disconnects that kill conversion rates. Works with Google, Meta, and LinkedIn ads.
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