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Scored across 45 tools
Each tool targets a distinct media generation task (e.g., text_to_video vs image_to_video) or lifecycle operation (create vs retrieve vs delete). Some related tools like face_swap_photo_create_image, head_swap_create_image, and body_swap_create_image are similar but descriptions clarify their specific inputs. The main risk is the large number of video/image creation tools, but the descriptions are distinct enough.
Naming follows multiple inconsistent patterns: some use 'ai_' prefixes (ai_image_generator_create_image), some use domain prefixes (video_projects_retrieve_details), some use feature-based prefixes (text_to_video_create_video), and a few are standalone (ping, saved_items_list). The verb_noun structure varies (e.g., 'create_video' vs 'retrieve_details' vs 'delete'). This lack of a uniform convention makes it harder for an agent to predict tool names.
With 45 tools, this is on the heavy side. The server covers a wide range of media generation features (video, image, audio) plus lifecycle utilities (upload, create, poll, wait, delete, fetch), which justifies many tools, but the count is high and near the threshold where agents may struggle to choose. It's borderline appropriate but not excessively bloated.
The server provides a complete lifecycle for each media type: presigned upload URLs, creation tools, retrieval of project details, wait helpers, download fetching, and deletion. There are also utilities for saved items, account info, and face detection. Minor gaps include no explicit list-projects tool (only saved items) and no cancel/update operations, but these are not essential for the core generation workflow.
