Single tool with clear naming (text_classify_content) and comprehensive description (194 chars). Input schema present with proper types and descriptions. However, output schema is completely undocumented, LLMs cannot plan downstream calls or extract structured data. No error handling guidance, no parameter constraints (categories array lacks item type), and no documentation of response fields (confidence scores, language, readability level, content type). Tool description is strong but schema completeness is weak.

• Document the complete output schema with all fields: categories (array of {name, confidence_score}), detected_language, flesch_kincaid_score, content_type. Include field types and descriptions so LLMs know what to expect.
• Add 'items' constraint to 'categories' parameter: {type: 'array', items: {type: 'string'}, description: '...'} to specify that array contains strings.
• Add error handling guidance: 'Returns 400 if text is under 50 characters. Returns 422 if custom categories are invalid. Returns 503 if classification service is unavailable, retry after 30 seconds.'
• Specify result limits in description: 'Returns top 3 categories ranked by confidence score (highest first). Confidence scores range from 0.0 to 1.0.'
• Reframe description to lead with positive use case: 'Use this to categorize text into predefined topics (tech, finance, health, sports, politics, entertainment, science, business). Returns top 3 categories with confidence scores, detected language, readability metrics, and content type. Ideal for content organization, tagging, and routing.'

Inferred effective spec: 2025-06-18+.

• Relies on Logging (deprecated) - log to stderr or use OpenTelemetry