Strong tool naming (verb_noun pattern), clear descriptions (avg 180 chars), and proper JSON Schema with type definitions. All 9 tools have descriptions and input schemas. Tool annotations present (readOnlyHint, destructiveHint, idempotentHint). Key gaps: parameter descriptions are minimal (avg 40 chars vs baseline 72), output schemas not formally documented, no pagination support for list_grills, and error handling lacks recovery guidance. Composition is clean, each tool has one responsibility. Security: credentials injected via environment variables (correct pattern).

• Document output schemas formally. For get_grill_status, define: {thing_name: string, friendly_name: string, device_type_id: string, status: {system_status: enum, grill_temperature: number, target_temperature: number, probe_temperature: number, pellet_level: number, units: enum, cook_timer_remaining: number}}.
• Expand parameter descriptions to 60 - 100 chars. Example: 'thing_name' → 'The grill's unique identifier (e.g., "ABC123DEF"). Call list_grills() first to discover available grills.' This guides LLM selection and reduces lookup errors.
• Add pagination to list_grills: optional 'limit' (1 - 100, default 50) and 'offset' (default 0) parameters. Return {grills: [...], total: N, offset: M} to support large account discovery.
• Enhance error messages with recovery hints. Wrap API calls in try-catch; on failure, return structured error: {error: 'grill_offline', message: 'Grill is offline. Check get_grill_status() to verify connectivity.', retryable: true}.
• Add confirmation pattern to shutdown_grill. Either require 'confirm=true' parameter with explicit description ('Must be true to prevent accidental shutdown'), or create a separate 'preview_shutdown' tool that returns the cool-down sequence without executing it.