Flattering ID Photo Edit

What It Solves

ID photos often suffer from uneven lighting, dull skin tone, or makeup and hair that do not photograph well, while still needing to preserve the person's identity. Flattering ID Photo Edit targets polished ID photos and professional portrait retouching, not influencer-style generation. It aims for soft lighting, clear skin texture, and more camera-ready styling while keeping the same person.

How It Works

The skill calls an HTTP image-editing API. A caller provides at least one reference portrait, fills in options such as gender, age, and beauty_level, submits an image_edit workflow, and polls until the task reaches succeeded before reading the result image URL. The main steps are:
- Validate input: prompt for an image when none is provided.
- Capture options: infer gender and age from the image, and choose natural / soft / glam when useful.
- Submit the task: use the fixed model and capability instead of composing long client-side prompt text.
- Handle payment and polling: retry the same request after a 402 payment step, then return data.result.data[].url on success.

Scope and Cautions

It fits ID photos and professional headshots with half-body composition. It is not suitable for heavy facial reconstruction, identity replacement, or inventing fictional people. Styling is mainly driven by the server-side recipe; if the result looks too heavy, retry with beauty_level=natural or add a note such as “more natural.”