| name | goose-product-photos |
| slug | goose-product-photos |
| description | GooseWorks Product Photos — turn a brand's product images into publish-ready photography (clean studio shots, lifestyle scenes, on-model looks) while keeping the product faithful (silhouette, materials, logo, colorway). You pick a brand + product and submit; the GooseWorks backend runs the SAME server-side pipeline the Product Photos studio uses (compose → generate → judge → auto-retry) and bills credits. Use when the user says "make product photos", "shoot my product", "studio/lifestyle/on-model photo of <product>", "generate product photography", or references a product to photograph. Unlike goose-ads (ad creative) this produces clean PRODUCT photos that can then feed the ad workflow.
|
| category | ads |
| version | 0.2.0 |
| author | GooseWorks |
| tags | ["gooseworks","ads","product-photos","photoshoot","product","ecommerce","studio","lifestyle","on-model"] |
GooseWorks Product Photos — branded product photography
The GooseWorks Product Photos skill. You pick a brand + product and submit one generation;
the backend runs the whole pipeline (compose the shot prompt → generate on gpt_image_2 →
judge for product fidelity → auto-retry a few times for free) and stores the results. You do NOT
generate images, call a model, or manage files — this is the exact same workflow the Product
Photos studio uses, so the skill and the app can never drift. The point is to enrich a brand's
usable product imagery — approved photos join the brand kit and can then feed the ad workflow
(goose-ads).
Prerequisite — the GooseWorks MCP server is REQUIRED
Everything goes through the mcp__gooseworks__* tools. If they are not available, stop and
tell the user to run gooseworks install --claude --mcp (and restart Claude Code). There is no
HTTP/file fallback.
Start from the brand context — don't re-ask what it already answers
If the gooseworks router handed you brand context, USE IT. If you were invoked directly, call
brand_get_context yourself first. It answers most of the setup questions below, so do not ask
the user for them:
- Which product? — the context's
products[] are the real catalog entries. Offer them; never
invent a product or ask the user to describe one you can already see.
- What does it look like / what is it made of? — grounded in the product's stored images and
description. Never guess a material, colorway, or silhouette.
- What vibe / who is it for? — the context's voice, positioning, and audience already say. Let
them shape the scene and styling instead of asking "what mood do you want?".
- Brand look — logo, colors, and fonts are owned by the backend research pass. Read them, never
re-derive them.
Ask only for the genuinely open choices: the shot category, how many photos, quality, and
whether a human model is wanted (which needs explicit consent — see the rules).
Identity & credits
- One agent-scoped token authenticates the tools; they resolve your org automatically. Never
print the token. (You may pass an optional
target to operate on a specific agent/org, exactly
as the other GooseWorks tools; omit it to use your pinned scope.)
- Credits are handled by the backend.
generate_product_photos reserves the estimated cost up
front and bills only the photos that pass the judge — , and a photo
the judge can't get right () is shown but . Call
first to quote the cost; shows the balance.
