Single tool with critical definition gaps. Tool name 'generate_ad_creatives' lacks action verb clarity (should be 'create_ad_creatives' or 'generate_social_ad_copy'). Description is adequate (89 chars) but parameters lack descriptions entirely, 'target_product' and 'platform' have no guidance on format, constraints, or usage. Input schema present but incomplete: platform has a default but no enum constraint despite being a platform selector. Output schema is undocumented, LLM cannot predict return structure. No error handling, validation, or recovery guidance. Tool appears to be a stub/mock implementation returning hardcoded values rather than a production-ready service.

• Add parameter descriptions: 'target_product: The product or service name (string, 1-200 chars). E.g. "AI Smart Watch", "SaaS project management tool". Used to generate contextually relevant ad copy.' and 'platform: The social media platform (enum: TikTok, Instagram Reels, Facebook, LinkedIn, YouTube Shorts). Determines ad format, length, and visual hook style.'
• Declare platform as an enum constraint instead of free-form string with default. This prevents LLM from inventing platform names.
• Document the output schema explicitly: 'Returns {ad_copy_variants: string[], visual_hooks: string[], predicted_ctr_score: number (0-10)}. ad_copy_variants is an array of 3-5 copy options optimized for the platform. visual_hooks are production-ready visual direction suggestions. predicted_ctr_score is a 0-10 CTR prediction based on historical performance data.'
• Implement actual ad generation logic instead of returning hardcoded mock data. Integrate with a real generative model or ad copy database.
• Add error handling: validate target_product length (1-200 chars), validate platform against enum, return actionable errors like 'Invalid platform: got "TikTok2". Must be one of: TikTok, Instagram Reels, Facebook, LinkedIn, YouTube Shorts.'