muapi-multi-angle-shots - SKILL.md Agent Skill

slug: muapi-multi-angle-shots name: muapi-multi-angle-shots version: "1.0.0" description: Generate a complete set of multi-angle product shots — front, side, back, top-down, and 45-degree perspective — for comprehensive product visualization. acceptLicenseTerms: true

Multi-Angle Shots

Generate a complete set of multi-angle product shots — front, side, back, top-down, and 45-degree perspective — for comprehensive product visualization.

Inputs

Name	Type	Required	Default	Description
`product_name`	text	yes	—	The product to photograph (e.g. "black leather sneaker", "glass perfume bottle", "smartwatch").
`product_image`	image_url	no	—	Optional reference product image to use as base.
`background_style`	text	no	pure white studio	Background/environment (e.g. "pure white studio", "dark moody grey", "natural marble surface", "lifestyle context").
`lighting`	text	no	soft studio lighting, product photography	Lighting style (e.g. "dramatic side lighting", "flat lay top-down", "rim lighting", "natural daylight").
`category`	text	no	general product	Product category to tailor angle logic (e.g. "footwear", "watch/jewelry", "electronics", "beverage bottle", "skincare").

Steps

Submit a single the plan with all angles in parallel.

All Angles (Parallel)

Front view — muapi image generate (model=ai-product-photography) if {{product_image}} provided, else muapi image generate (model=nano-banana-pro):
- Prompt: {{product_name}} — perfectly centered FRONT VIEW, eye-level angle. {{background_style}} background. {{lighting}}. Sharp focus, commercial product photography, ultra detailed, no props.
- Aspect ratio: 1:1
Side / 3/4 angle view — same model as step 1:
- Prompt: {{product_name}} — elegant 3/4 SIDE ANGLE view, slight perspective showing depth and form. {{background_style}} background. {{lighting}}. Shows product silhouette and side detail, commercial photography.
- Aspect ratio: 1:1
Back view — same model as step 1:
- Prompt: {{product_name}} — BACK VIEW, centered, showing rear details, finishes, and labels if any. {{background_style}} background. {{lighting}}. Product photography, equal detail to front shot.
- Aspect ratio: 1:1
Top-down / flat lay — muapi image generate (model=ai-product-shot) if {{product_image}} provided, else muapi image generate (model=bytedance-seedream-v4.5):
- Prompt: {{product_name}} — perfectly overhead TOP-DOWN flat lay view, camera pointing straight down. {{background_style}} surface. Flat lay product photography, even lighting, no shadows at edges, symmetrically placed.
- Aspect ratio: 1:1
Hero glamour shot — muapi image generate (model=nano-banana-pro):
- Prompt: {{product_name}} — dynamic low-angle HERO SHOT, slightly below eye level looking up at product. Dramatic {{lighting}}, slight depth of field, editorial product photography. {{background_style}} background. Premium commercial advertising quality.
- Aspect ratio: 4:5

After generation:

Present all 5 angles in a grid layout description
Suggest adding a 360° spin video with kling-v3.0-pro-image-to-video
Offer to upscale any angle with ai-image-upscaler

Notes

For footwear: emphasize sole view as a 6th angle if requested.
For watches/jewelry: suggest a macro detail shot as an additional step.
For electronics: add "showing all ports, buttons, and screen" to front and side prompts.
ai-product-photography is ideal when a reference image is provided — it preserves product identity.

Trigger Keywords

multi angle, multiple angles, 360 product, product angles, all sides, front back side, product views, angle shots, product photography set

Notes for the Executing Agent

This recipe is LLM-orchestrated: read each phase, gather any missing inputs from the user, then call muapi CLI commands. Use muapi auth configure first if MUAPI_API_KEY is unset.
For model IDs without a CLI alias yet, fall back to the raw endpoint via curl -X POST https://api.muapi.ai/api/v1/<endpoint> -H "x-api-key: $MUAPI_API_KEY" -H 'content-type: application/json' -d '{...}' and poll with muapi predict wait <request_id>.
Substitute {{input_name}} placeholders with the user's actual inputs before issuing each call.