17 tools with basic schemas and descriptions, but significant gaps in parameter documentation and output schema clarity. All tools are READ_ONLY and follow verb_noun naming (get_*, list_). Descriptions exist but are often generic (10-50 chars) and lack actionable context for LLM selection. Parameter descriptions are sparse or missing entirely. No output schemas documented. Error handling is minimal, API errors return generic {'error': str(e)} with no recovery guidance. Tool composition is reasonable (single responsibility), but parameter naming inconsistencies (e.g., 'identifiers' as comma-separated string vs structured array) and missing type constraints (enums for period, classification_name) force LLM guessing. Baseline: avg tool description ~40 chars (well below 194-char production baseline); ~60% of params lack descriptions.

• Add output schema documentation for each tool. Example: 'Returns array of {story_uuid: string, title: string, url: string, sentiment: string, source_name: string}'. This enables agents to extract and chain results.
• Convert free-form string parameters to enums where applicable. Replace 'period' default 'd1' with enum: ['d1', 'd7', 'd30', 'y1'] and document each. Replace 'classification_name' with enum: ['NAICS', 'GICS', 'ICB'].
• Expand tool descriptions to 80-150 chars with explicit selection criteria. Example: 'Get latest financial news for a ticker or topic. Use this to find recent market sentiment and breaking news. Returns up to N stories with sentiment scores and source credibility.'
• Implement structured error responses: {'error': string, 'code': string, 'retryable': boolean, 'suggestion': string}. Example: {'error': 'Invalid ticker', 'code': 'INVALID_INPUT', 'retryable': false, 'suggestion': 'Call list_sectors() to find valid identifiers.'}
• Add pagination support: accept 'offset' and 'limit' (or 'page' and 'per_page'), return 'total_count' and 'has_more' in responses. Document in tool descriptions: 'Supports pagination; default limit=5, max=100.'