The server implements 16 well-defined tools with mostly complete schemas and descriptions. All tools have explicit input schemas with types and parameter descriptions. Most tool names follow verb_noun conventions (chat_completion, list_models, delete_conversation). Descriptions are generally 50-150 characters, within the 10-1024 character baseline range. However, several quality gaps prevent a higher score: (1) some descriptions lack actionable guidance about when/why to use a tool vs similar ones (e.g., chat_completion vs chat_with_gpt distinction unclear); (2) no documented output schemas for any tool, LLMs cannot predict return structure without explicit documentation; (3) error handling guidance is absent, no indication of retryability, user-fixable vs fatal errors, or recovery paths; (4) security risks around credentials (server connects to ChatGPT web via CDP, but parameter descriptions do not clarify if auth tokens/sessions are server-managed or exposed); (5) composition concerns, some tools could be batched (e.g., delete_conversation takes one ID at a time, no batch delete). The naming is clear (all tools are unambiguous), and parameter constraints are present (enums, defaults, min/max where relevant). This is a solid B-range implementation with good naming and schema coverage but missing the documentation depth required for A-range (output schema docs, error guidance, security clarification).

• Add explicit output schema documentation to every tool. Example for chat_completion: 'Returns {choices: [{message: {content: string, role: string}, finish_reason: string}], conversation_id: string, model: string}. The conversation_id can be passed to subsequent chat_completion calls to continue the conversation.'
• Add confirmation or dry-run step to delete_conversation, delete_project, and delete_memory. Example: Add parameter 'confirm: boolean' with description 'Set to true to confirm permanent deletion. If false, returns what would be deleted without executing.'
• Document dependencies and discovery flows. Update list_models description to: 'List all available model slugs. Call this first to discover available models before passing model parameter to chat_completion. Returns list of {slug: string, description: string, context_window: integer}.'
• Clarify tool distinction. Update chat_completion to: 'Send a message to ChatGPT (the conversational AI). Use this for general conversations. Use chat_with_gpt instead to interact with custom-trained GPTs created via the Projects feature.'
• Add error handling guidance to all tools that interact with ChatGPT. Example for chat_completion: 'On rate limit (429), retry after waiting. On auth failure (401), your session may have expired, restart the server. On model error (500), the model may be temporarily unavailable.'
• Document return structure for pagination. Update get_conversation to include in description: 'Returns {messages: [{id: string, role: string, content: string, created_at: string}, ...], has_more: boolean, total: integer}. Use offset and limit to page through long conversations.'

Inferred effective spec: 2025-06-18+.

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