Critical gaps across all dimensions. Tool definitions lack input schemas (only 3 of 25 tools show any schema), descriptions are minimal (most under 50 chars), and parameter documentation is absent. No evidence of error handling guidance, output schema documentation, or security patterns. The server exposes 25 tools with almost no structured metadata for LLM consumption. This is far below production baseline.

• Add complete JSON Schema input definitions for all 25 tools. Include type, description, and constraints (enum, minLength, pattern) for every parameter. Example: auth_send_code should define 'email' (type: string, format: email, description: 'Email address to send code to').
• Expand all tool descriptions to 100-200 characters. Include: (1) what the tool does, (2) when to use it vs similar tools, (3) prerequisites or dependencies, (4) what it returns. Example: 'Send a one-time authentication code to the user's email. Call this first to initiate login. Returns a challenge_id needed for auth_verify_code.'
• Document output schemas for all tools. Specify which fields are returned, their types, and which are required for chaining. Example: agent_issue should return {agent_id, agent_name, created_at, status} so downstream tools can reference agent_id.
• Add error handling guidance to destructive tools (delete, revoke, logout). Specify: (1) what errors are possible, (2) which are retryable, (3) what the LLM should do on failure. Example: 'api_key_revoke: Returns 404 if key not found (user-fixable: verify key_id), 403 if not authorized (fatal), 200 on success (idempotent).'
• Document permission requirements and scope declarations for each tool. Example: 'auth_logout requires scope:write:auth. admin_domain_reverify requires scope:admin. Audit all calls for compliance.' This enables least-privilege agent configuration.