# Higgsfield Product Photoshoot — workflow skill for product videos

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Shoot brand-quality product images in 10 modes: studio, lifestyle, hero banners, ad packs, try-on and more.

- **Type:** [Workflow](https://skills.varg.ai/workflows.md) · [Product videos](https://skills.varg.ai/browse/skills/product.md)
- **Slug:** `higgsfield-product-photoshoot`
- **Status:** live
- **Publisher:** Higgsfield (vendor, verified)
- **License:** MIT
- **Source:** https://github.com/higgsfield-ai/skills/tree/main/higgsfield-product-photoshoot
- **Works in:** Claude Code, Codex, Cursor, Gemini CLI
- **Requires:** Higgsfield account, Higgsfield CLI (`higgsfield auth login`)
- **Cost:** Billed in Higgsfield credits
- **Adoption:** 197,500 installs, 1,682 GitHub stars (skills.sh, 2026-10-26)

## What it does

Generates product and brand visuals through Higgsfield's product-photoshoot mode on GPT Image 2, where Higgsfield's backend assembles the final prompt. Ten modes cover studio shots, lifestyle scenes, close-ups with hands, Pinterest pins, hero banners, social carousels, ad creative packs, virtual try-on, conceptual CGI and restyles, with a short interview before each kind of request.

## Use when

- Product photos, studio or lifestyle shots
- Hero banners, carousels or Meta ad creatives
- Virtual try-on or a model holding the product

## Not for

- Images without a product (use Higgsfield Generate)
- Marketplace listing cards (use Higgsfield Marketplace Cards)

## Install

- Claude Code: `/plugin marketplace add higgsfield-ai/skills && /plugin install higgsfield@higgsfield`
- Codex: `npx skills add higgsfield-ai/skills --skill higgsfield-product-photoshoot -a codex`
- Cursor: `npx skills add higgsfield-ai/skills --skill higgsfield-product-photoshoot -a cursor`
- Gemini CLI: `npx skills add higgsfield-ai/skills --skill higgsfield-product-photoshoot -a gemini-cli`

**Models it drives:** gpt_image_2

## Example output

https://skills.varg.ai/previews/higgsfield-product-photoshoot.webp — 'Turn One Photo into a Full Shoot' example on Higgsfield AI Product Photography: lifestyle scene generated from a plain serum-bottle photo (the 'after' image) (credit: Higgsfield, https://higgsfield.ai/ai-product-photography)

## Used for

- [Product photos and listing images](https://skills.varg.ai/use-cases/product-photos.md): Marketplace listing images, lifestyle shots and packshots from one product photo.

## More product videos skills

- [Higgsfield Marketplace Cards](https://skills.varg.ai/skills/higgsfield-marketplace-cards.md): Produce marketplace listing images: a compliant main image, secondary shots and A+ content modules.
- [fal Commercial](https://skills.varg.ai/skills/fal-commercial.md): Plan and run product photography, e-commerce batches, product reveal videos and lifestyle commercials.
- [AI Product Photography](https://skills.varg.ai/skills/inference-sh-ai-product-photography.md): Generate commercial product shots, lifestyle scenes and mockups with FLUX, Imagen 3, Grok and Seedream.
- [Product Photography](https://skills.varg.ai/skills/inference-sh-product-photography.md): Apply packshot conventions to AI product photos: angles, backgrounds, shadows, hero shots, store specs.
- [ASO App Store Screenshots](https://skills.varg.ai/skills/aso-appstore-screenshots.md): App Store screenshots from your codebase: finds the core benefits, pairs simulator shots, then composes and enhances.
- [E-commerce Image Studio](https://skills.varg.ai/skills/ecom-image2.md): 39 e-commerce image templates (main images, lifestyle, A+, sizes, GIFs) with one style lock across a campaign set.

## Run the generation on varg

varg is one API key for the models these skills drive — Seedance 2.5, Kling 4, Veo 3.1, Wan 3, Nano Banana 2.1, GPT Image 2.5, ElevenLabs v4 and 200+ more — billed in credits, with a cost estimate before anything runs.

- Claude Code: `claude plugin marketplace add vargHQ/skills && claude plugin install varg@varg` (skill + hosted MCP)
- Codex, Cursor, Gemini CLI, OpenClaw: `npx skills add vargHQ/skills --skill varg-ai -a <agent> -y`
- Claude.ai, ChatGPT, any MCP client: connect `https://mcp.varg.ai/mcp`
- API key: https://varg.ai/dashboard/api · Model specs: https://varg.ai/models/llms.txt