Critical failures across naming, descriptions, and schemas. Tool names lack action verbs (show_reasoning, verify_paint_open are weak; verify_calculation/verify_consistency are vague). Descriptions are present but generic (10-50 chars, well below 50-200 char baseline for LLM optimization). Input schemas visible but severely incomplete: most parameters lack type constraints; list parameters have no item type specification; no output schemas documented. Tools 3-4 defined in mcp_client.py (not server) suggest inferred registration. No error handling guidance, no pagination support, no field documentation for responses. Inconsistent return types (dict vs TextContent vs TextContent wrapped in dict). Code shows incomplete implementation (verify_consistency has truncated logic, undefined consistency_score variable).

• Rename tools with clear action verbs: 'display_reasoning_steps', 'check_paint_status', 'validate_calculation', 'check_step_consistency'. Follow verb_noun convention.
• Document output schemas for all tools. E.g., add() returns {result: number, operands: [number, number]}. Specify field types and meanings so LLMs can chain calls.
• Expand descriptions to 50-200 chars. Current descriptions (10-40 chars) lack context. E.g., 'Verify if a calculation is correct' → 'Verify if a mathematical expression evaluates to the expected result. Returns true if |actual - expected| < 1e-10, false otherwise. Use to validate intermediate steps in multi-step calculations.'
• Fix verify_consistency implementation. Complete the consistency_score calculation and return a structured result with {is_consistent: boolean, issues: [string], warnings: [string]}.
• Add error handling with recovery guidance. E.g., divide() should return {error: 'Division by zero', suggestion: 'Check divisor parameter; ensure it is non-zero'} instead of raw exception.