--- title: "Studio product shot — Meleon Skill" description: "Turn a casual product photo into a marketplace-ready pack shot on pure white, with the product kept pixel-for-pixel as photographed. Removes the background, scales the product to fill 85% of the frame, adds a soft natural contact shadow, and checks the result against Amazon and Shopify rules. Square 1:1 and 4:5, 2000 px." url: https://meleon.ai/skills/studio-product-shot/ author: "Meleon AI" --- # Studio product shot > Turn any product photo into a clean, marketplace-ready shot on pure white. - Type: Image Skill - Category: Product photos - Version: 1.0.0 (updated 2026-10-16) - Made by: Meleon AI (official) - Price: Free to download. Outside costs: Background removal costs about one cent per photo on fal. Everything else runs locally for free. - Runs in: Claude Code, Codex and Cursor - Page: https://meleon.ai/skills/studio-product-shot/ - Download: https://meleon.ai/downloads/studio-product-shot.zip - Manifest: https://meleon.ai/skills/studio-product-shot.json ## What it does Turn a casual product photo into a marketplace-ready pack shot on pure white, with the product kept pixel-for-pixel as photographed. Removes the background, scales the product to fill 85% of the frame, adds a soft natural contact shadow, and checks the result against Amazon and Shopify rules. Square 1:1 and 4:5, 2000 px. ## Made for - E-commerce sellers - Brands - Marketplace sellers - Agencies ## Before you start - You give it: Product photo - You need: Node.js 20.9 or newer (sharp needs it); run `npm install sharp` in the Skill folder for compose-white.mjs and check-spec.mjs. A background-removal model; or your own FAL_KEY to call the one named in assets/generation-input.json. - Cost per run: Background removal costs about one cent per photo on fal. Everything else runs locally for free. - Makes: Background removal (fal-ai/birefnet/v2) and local compositing, 1:1 or 4:5 ## Install Run the command for your agent in a terminal. It downloads https://meleon.ai/downloads/studio-product-shot.zip and unzips it into the agent's personal Skills folder. ### Claude Code ```sh mkdir -p ~/.claude/skills && curl -fsSL https://meleon.ai/downloads/studio-product-shot.zip -o /tmp/studio-product-shot.zip && unzip -o /tmp/studio-product-shot.zip -d ~/.claude/skills ``` Then ask Claude Code to use it: `/studio-product-shot`. ### Codex ```sh mkdir -p ~/.agents/skills && curl -fsSL https://meleon.ai/downloads/studio-product-shot.zip -o /tmp/studio-product-shot.zip && unzip -o /tmp/studio-product-shot.zip -d ~/.agents/skills ``` Then ask Codex to use it: `$studio-product-shot`. ### Cursor ```sh mkdir -p ~/.cursor/skills && curl -fsSL https://meleon.ai/downloads/studio-product-shot.zip -o /tmp/studio-product-shot.zip && unzip -o /tmp/studio-product-shot.zip -d ~/.cursor/skills ``` Then ask Cursor to use it: `/studio-product-shot`. ## Example request ```text /studio-product-shot my sneaker photo, square, for an Amazon listing ``` In Codex, start with `$studio-product-shot` instead of `/studio-product-shot`. ## Files Every file in the package, readable before you install: - [SKILL.md](https://meleon.ai/skills/studio-product-shot/files/SKILL.md) (5.4 KB) - [references/output-spec.md](https://meleon.ai/skills/studio-product-shot/files/references/output-spec.md) (1.2 KB) - [references/shot-guide.md](https://meleon.ai/skills/studio-product-shot/files/references/shot-guide.md) (5.0 KB) - [assets/example-input.webp](https://meleon.ai/skills/studio-product-shot/files/assets/example-input.webp) (101.0 KB) - [assets/generation-input.json](https://meleon.ai/skills/studio-product-shot/files/assets/generation-input.json) (706 bytes) - [assets/preview.webp](https://meleon.ai/skills/studio-product-shot/files/assets/preview.webp) (71.1 KB) - [assets/prompt-template.md](https://meleon.ai/skills/studio-product-shot/files/assets/prompt-template.md) (551 bytes) - [scripts/build-cutout-input.mjs](https://meleon.ai/skills/studio-product-shot/files/scripts/build-cutout-input.mjs) (1.0 KB) - [scripts/check-spec.mjs](https://meleon.ai/skills/studio-product-shot/files/scripts/check-spec.mjs) (4.0 KB) - [scripts/compose-white.mjs](https://meleon.ai/skills/studio-product-shot/files/scripts/compose-white.mjs) (7.3 KB) ## Versions - 1.0.0 (2026-10-16) ## Instructions (SKILL.md) Use this skill when someone has a casual photo of a real product and needs a marketplace listing image: the product on pure white, large in the frame, with a believable soft shadow, exactly as it looks in real life. The product is never redrawn. A model cuts it out of the photo, and a script places those same pixels on white. Labels, stitching and colours cannot drift. ### What you need - One product photo, as a file or public URL. Whole product in frame, in focus, ideally on a surface that contrasts with it. - The ratio: 1:1 (default) or 4:5. - Optional: no shadow, for platforms that forbid it. If the photo is missing, ask for it. Do not invent the product. ### What you make - A 2000 x 2000 JPEG on pure white (#FFFFFF), product filling about 85%, with a soft contact shadow. Default. - A 2000 x 2500 4:5 JPEG, when asked. - A pass/fail spec check for the file. ### How to run it 1. Read `references/shot-guide.md` for source-photo advice, marketplace rules and the product-type notes (shiny, transparent, white-on-white, dark, tiny). If the photo has hands, stickers or clutter touching the product, tell the person before you start. 2. Make the photo reachable. If it is a local file, upload it to a temporary host you control to get a public https URL (or send it as a data URI), and delete it afterwards. Run `node scripts/build-cutout-input.mjs --image `. POST the printed JSON `input` to fal model `fal-ai/birefnet/v2` with the person's own `FAL_KEY` (this Skill never stores keys). The response holds the transparent PNG at `image.url`: download that file. Without a key, use any background-removal tool that returns a transparent PNG (rembg or BiRefNet class) and go to step 3. 3. Look at the cut-out. Check the edge: no halo, nothing missing, nothing extra. 4. Run `node scripts/compose-white.mjs --input cutout.png --output shot.jpg`. Add `--ratio 4:5` for portrait, `--shadow 0` for no shadow, `--normalise` for a dull, underexposed photo of a light product (one gain on all channels, hue unchanged; look at the product colour afterwards and drop the flag if it shifted). The defaults (2000 px, 85% fill, shadow 0.45, no normalise) are what produced `assets/preview.webp`. 5. Run `node scripts/check-spec.mjs shot.jpg`. The five required checks must pass; the shadow line is a note. Fill is measured from `shot.jpg.json`, which compose-white.mjs writes next to the shot. For white-on-white products judge the edge and fill by eye. 6. Compare the shot with the original photo side by side (`references/output-spec.md`, checks 6 to 9). The product must be the same. 7. If a check fails: max 3 attempts, change one thing per attempt (the fix from `references/shot-guide.md`, or the cleanup fallback in `assets/generation-input.json`, and say what you changed), view each output beside the input, then return the best one and say what still differs. Never return a shot that misrepresents the product. 8. Return the file and say which checks passed. ### Limits - The photo's exposure is kept. A dull phone photo gives greyish whites. `--normalise` lifts light products a little; it cannot fix a badly lit photo. - The cleanup fallback regenerates the product pixels. The result is no longer a photographic cut-out: say so when you return it. ### Files - `references/shot-guide.md`: source photos, marketplace rules, shadow and fill settings, fixes for bad cut-outs. - `references/output-spec.md`: sizes, format and the pass/fail checklist. - `assets/generation-input.json`: the cut-out model and its settings. - `assets/prompt-template.md`: the optional cleanup prompt, for the rare case the matte cannot fix. - `assets/example-input.webp` and `assets/preview.webp`: a real input photo and the shot made from it. - `scripts/build-cutout-input.mjs`: prints the background-removal request. It does not call any API. - `scripts/compose-white.mjs`: places the cut-out on pure white with a shadow, and writes `.json` with the product box. Needs `sharp`. - `scripts/check-spec.mjs`: checks the white border, fill, ratio and size. Needs `sharp`. ## Related - [Lifestyle product scene](https://meleon.ai/skills/lifestyle-product-scene.md): Put your real product into a believable lifestyle scene without a photoshoot. - [Packaging mockup](https://meleon.ai/skills/packaging-mockup.md): See your flat packaging art as a real, photographed product. - [Product colour variants](https://meleon.ai/skills/product-colour-variants.md): Turn one product photo into a set of colourways with everything else locked. - [All Meleon Skills](https://meleon.ai/skills/) (index as JSON: https://meleon.ai/skills.json; site guide: https://meleon.ai/llms.txt)