Critical gaps across all dimensions. Tool definitions are severely underdeveloped: descriptions are present but generic (avg ~80 chars, well below 194-char baseline); input schemas lack parameter descriptions entirely; no output schemas documented; no error handling guidance; no tool annotations. The server acts as a bridge to external agents (Agent Zero, Claude, Codex) but exposes their capabilities without proper abstraction or LLM-optimized wrapping. Source code provided is incomplete (agent_zero_mcp_stdio.py truncated), preventing full verification of implementation. Naming is acceptable (verb-noun pattern) but parameter documentation is absent.

• Add 50 - 150 character descriptions to every parameter. E.g., for 'message' in send_message: 'The task or query to send to Agent Zero. Can include file paths, code snippets, or natural language instructions. Agent Zero will execute in an isolated Linux environment.'
• Document output schemas for all tools. Specify returned fields, types, and whether results are paginated. E.g., send_message should return {status: string, result: string, execution_time_ms: number}.
• Add tool annotations: mark send_message, codex, codex_reply, codex_task with destructiveHint=true; mark claude_query, claude_code_review with readOnlyHint=true.
• Expand tool descriptions to 150 - 250 chars. Include: what the tool does, when to use it (vs similar tools), and what it returns. E.g., 'Send a task to Agent Zero for execution in an isolated Linux environment. Use for file operations, command execution, or code generation. Returns execution status and output.'
• Add error handling guidance: document common failure modes (timeout, invalid task, agent unavailable) and recovery steps (retry with shorter timeout, validate input, check agent connectivity).

Inferred effective spec: <=2025-11-25.

• Relies on Logging (deprecated) - log to stderr or use OpenTelemetry