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Scored across 32 tools
Several tools are near-duplicates or have overlapping purposes: create_image and create_image_file both say 'Creates an image given a prompt,' and edit_image and edit_image_file share identical descriptions. Provider-specific response tools (create_chat_completion, create_anthropic_message, create_gemini_content, create_response) and model/pricing discovery tools (get_pricing, get_model_pricing, compare_models, list_models, get_model) force agents to guess which one fits a given request.
Every tool uses lowercase snake_case, and the names consistently follow a verb_noun pattern (create_, get_, list_, retrieve_, delete_, cancel_, edit_, compare_, etc.). There are no mixed conventions such as camelCase or vague standalone verbs.
32 tools is above the typical well-scoped range and crosses the 'too many' threshold. The broad TokenLab platform explains some breadth, but redundant image/file aliases and multiple provider-specific generation tools inflate the surface beyond what an agent can easily navigate.
The surface covers a wide AI platform: chat completions, embeddings, image generation/editing, speech, transcription, translation, video, music, 3D, files, models, pricing, async task status, and decision evaluation. Minor gaps exist, notably cancel_task only supports queued Seedance video tasks and there are no update operations for file/model resources, but core workflows are broadly covered.
