Server has 4 tools with basic schemas and descriptions, but significant gaps limit production readiness. All tools have descriptions (10-60 chars, below ideal 50-200 char range) and input schemas with type definitions. However, parameter descriptions are minimal or missing context. No output schemas documented. Error handling is absent, tools do not guide recovery or categorize failures. No tool annotations (readOnlyHint, destructiveHint, idempotentHint) despite WRITE/REVERSIBLE risk levels. Naming is verb-forward (execute-*, install-*, cleanup-*) but descriptions lack WHEN/WHY context and do not explain state management or session lifecycle. Missing: pagination guidance, rate limits, permission gates, audit trail documentation, and recovery patterns.

• Add output schemas to all tools. Document return type (e.g., {type: 'object', properties: {output: {type: 'string'}, exit_code: {type: 'integer'}, error: {type: 'string'}}}). This enables LLMs to chain tools and extract results reliably.
• Expand tool descriptions to 100-200 chars. For execute-persistent, add: 'Executes Python code in a persistent Docker container. Session state persists across calls. Use session_id to resume. Call cleanup-session to free resources.'
• Add destructiveHint: true to cleanup-session and idempotentHint: true to execute-transient. This signals to agents which tools are safe to retry and which have irreversible side effects.
• Document the 'state' parameter schema in execute-transient. Specify: object properties (e.g., variables, imports), serialization format (JSON), and size limits. Example: {type: 'object', additionalProperties: true, description: 'Python variables to inject into execution context'}.
• Add error handling guidance in tool descriptions. E.g., 'If Docker container fails to start, check server logs. If code times out (>30s), simplify the code or increase timeout via config.'

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

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