14 tools with consistent verb-noun naming (get_*, search) and basic descriptions. However, critical gaps: (1) Most parameter descriptions are minimal (1-5 words), violating the 72-char baseline for param annotations. (2) No output schemas documented, LLMs cannot infer response structure. (3) No enum constraints on multi-value params (e.g., instrument_type, news type, screener type accept free-form strings). (4) Error handling is generic ('Unable to fetch X') with no recovery guidance. (5) All tools return JSON strings rather than structured objects, forcing LLM parsing. Naming is solid (90% start with action verbs), but descriptions and schemas lag production baselines.

• Document output schemas for all tools. Specify field names, types, and structure. E.g., search returns [{symbol, name, type, exchange}], get_market_quotes returns {symbol, price, change, changePercent, ...}. Use JSON Schema in tool metadata.
• Expand parameter descriptions to 50-100 chars. Include format, constraints, and examples. E.g., 'instrument_type: One of STOCKS, ETF, or MUTUALFUNDS. Determines which market data endpoint is queried.' instead of 'The type of the instrument, STOCKS/ETF/MUTUALFUNDS.'
• Add enum constraints to multi-value parameters. Convert 'type' in get_market_news to enum: [ALL, VIDEO, PRESS_RELEASE]. Convert screener 'type' to enum with all 9 valid options. Prevents LLM hallucination.
• Enhance error messages with recovery guidance. E.g., 'Symbol INVALID not found. Try search(query="company name") to find the correct ticker.' or 'API rate limit exceeded. Retry in 60 seconds.' Categorize as retryable vs user-fixable.
• Add pagination support. Accept optional limit (default 20, max 100) and offset/cursor params. Return total_count and next_cursor in response. Allows agents to iterate through large result sets without context explosion.