Product Photoshoot Workflow

Product Photoshoot Workflow

Turn one product reference photo into a brand-ready set matching the requested count, each emphasizing a different sales angle.

Optional assistant scope

Use this planning workflow only when the caller asks for creative development. A supplied storyboard, prompt set or approved count/budget can call tools directly. Preserve explicit tool/model/provider, prompt, ratio, references and quality choices. Do not impose a new concept-selection or approval step on resolved inputs. Discovery is available to any workflow; delegation is optional. Return handles/results to the caller, which owns previews, downloads and presentation. Visual descriptions require actual inspection.

Choosing a dedicated Skill

When choosing a tool for an unresolved request, prefer the dedicated workflow: for transparent cutouts use remove_background; for ecommerce detail images use generate_product_detail_images; for posters use generate_marketing_poster; for white, smart or custom product backgrounds use generate_ai_background; for still-image upscaling use upscale_image. Call these tools directly. Do not route them through generic prompt enhancement, preference loading or image-generation agents. Preserve an upstream workflow's explicit tool selection. They require MeiGen credentials and purchased credits; OpenAI-compatible providers cannot run them. No daily free credits or Web free attempts apply.

Use list_skills for current inputs, defaults and prices. Ask only for missing required information or unresolved output scope. An explicit requested count/modules/quality already authorizes that scope; do not reconfirm it or add paid images. Product Detail MCP requires explicit modules (use [] for custom modules only); each selected module is one image. Posters need only a subject; images and copy are optional. Use defaults for unspecified settings and never invent product facts, dates or discounts.

Use real accessible images only. Both remote and local connections expose upload_skill_image; local npm also accepts real file paths for the four ordinary image-input workflows. If the host cannot read an attachment, ask for a public direct HTTPS image URL; never invent paths or base64.

Upscale is a separate original-image path: pass the original public direct HTTPS PNG/JPEG/WebP URL as imageUrl, at most 64 MiB and 64 MP. Local npm also accepts an actual original PNG/JPEG/WebP path in imageUrl through its dedicated upload route, preserving source dimensions. For readable attachment bytes, call upload_skill_image with purpose: "upscale" (base64 up to 3 MiB decoded); use the returned imageUrl. Do not use purpose: "reference" or generic reference compression for Upscale. If the host cannot read the attachment, request a real public original-image URL. On every MCP submission, including the first, pass confirmedCredits from the live list_skills quote within the user or upstream workflow accepted budget; reuse an already explicit acceptance. This pre-dispatch recheck is not an atomic spending cap. Use mode: "crisp" (default) or "creative" as offered by list_skills. allowDownscale is opt-in: explain that it permits preprocessing to at most 4096px/16 MP and the final output can be smaller than the original; set it only after the user explicitly accepts that tradeoff. Upscale accepts still images, not video. For upscale_resize_required or price_changed, return the resize/cost decision to the caller. Reuse an already explicit acceptance; otherwise obtain acceptance of the new tradeoff or price before submitting a new requestId with accepted allowDownscale and confirmedCredits. These are changed, confirmed inputs—not a blind retry of an interrupted submission.

The caller generates and persists requestId for each logical step. For interrupted submissions, call check_skill with the original skill/ID before retrying. Follow nextAction, including waiting afterSeconds; retry only when instructed, using its exact original ID and parameters. Never use a new ID as a blind retry or automatically pay for failed-module replacements. Auth/payment/input rejections require their indicated action instead of polling. Return structured status, task handles and completed image URLs to the caller, with failed modules and refund states separately. The caller owns display and downloads; end users do not need to manage technical IDs.

When to trigger

• User uploads a product photo and says "make e-commerce images", "design a campaign", "I need product shots"
• User says 电商产品图 / 产品多角度图 / 产品拍摄 / 产品营销图
• Anyone asking for "a set of product images" with a reference attached

Prerequisites

1. A reference image is required — the user MUST provide a product photo (URL or local path). If they have not, ask once: "Please share the product photo you want me to work from." Do NOT try to invent a product without a reference.
2. For the generic photoshoot below, check the installed connection first: remote MeiGen uses OAuth; existing local npm may use MeiGen or OpenAI-compatible credentials. Dedicated Skills require MeiGen. If disconnected, follow the host-specific setup guide; /meigen:setup is available only in the Claude plugin.

The 4 directions

These four directions are optional starting points. Match the requested count and existing plan. Ask which directions to use only if that choice is unresolved; do not reconfirm an approved set.