{"code":0,"data":{"id":"390a857d-980b-4e2b-a1b8-572f06d5274e","publisher_type":"individual","publisher_unique_handle":"evanchen","creator_email":"cyefan2@gmail.com","template_name":"nanobanana Image Capture Labeling","icon":"","icon_background":"","icon_file_key":"templates/390a857d-980b-4e2b-a1b8-572f06d5274e/icon.png","kind":"sandboxed","dsl_file_key":"templates/390a857d-980b-4e2b-a1b8-572f06d5274e/dsl.zip","dsl_raw_file_key":"templates/390a857d-980b-4e2b-a1b8-572f06d5274e/dsl_raw.yaml","asset_files":null,"asset_tree_nodes":null,"categories":["design"],"deps_plugins":["langgenius/anthropic","langgenius/gemini_image"],"preferred_languages":["en"],"overview":"This is a skill used for calorie intake calculation that analyzes images uploaded by users.\r\n\r\nBased on the numerical analysis of three nutritional components—sugar, protein, and fat—the data is sent to NanoBanana. NanoBanana then overlays the analysis of these three nutrients as annotations directly onto the image.","readme":"You will need to use at least one LLM provider and obtain a NanoBanana API key. \r\n\r\nThis workflow can also be utilized for other image-to-image modification tasks, as it is built on an Image-to-Image (Img2Img) framework.","partner_link":"","version":"0.6.0","status":"published","review_comment":"","usage_count":1096,"created_at":"2026-02-14T07:07:25.240188Z","updated_at":"2026-02-14T07:07:30.519823Z"},"msg":"ok"}