Deep Flo provides 6 tools with basic schemas and descriptions, but falls short of production quality. Tool names are clear and action-oriented (deep_flo_research, web_search, fetch_url, search_openalex, search_semantic_scholar). Descriptions exist but are brief (34 - 194 chars, within baseline range). Input schemas are present with type definitions and parameter descriptions. However, output schemas are not documented, critical for LLM planning. Error handling is absent; tools do not guide recovery or categorize failures. No tool annotations (readOnlyHint, destructiveHint, idempotentHint) despite all being read-only. Parameter descriptions lack format constraints (e.g., max_results ranges, URL format validation). The deep_flo_research tool accepts a thread_id with a default but no explanation of what thread_id controls or how it affects behavior. Academic search tools (search_openalex, search_semantic_scholar) have identical schemas and descriptions, LLMs cannot distinguish when to use each. Missing: output field documentation, error recovery guidance, and tool-specific differentiation.

• Document output schemas for all tools. Example: web_search should return {results: [{title, url, snippet, source}], total_count: int}. Include field types and descriptions so LLMs know what to extract.
• Add error handling with recovery guidance. Example: 'If web_search fails with timeout, try a simpler query or use fetch_url directly on a known source.'
• Differentiate search_openalex and search_semantic_scholar in descriptions. Explain when to use each: 'Use OpenAlex for sociology/social science; use Semantic Scholar for CS and interdisciplinary work.'
• Add parameter constraints to descriptions. Example: max_results (1 - 100, default 5), from_year (1900 - current year), URL format (must start with http:// or https://).
• Add readOnlyHint annotations to all tools in the MCP tool definition to signal safety to agents.