The Garak MCP server has significant definition quality gaps. While 5 tools are explicitly registered with descriptions, most descriptions are generic and lack the specificity needed for LLM tool selection. Parameter descriptions are minimal or missing. Output schemas are not documented. The tool set is focused but lacks idempotency guidance and error recovery patterns. Average tool score: 42/100.

• Add enum constraint to model_type parameter in list_models and run_attack: {"type": "string", "enum": ["ollama", "openai", "huggingface", "ggml"]}
• Document output schemas for all tools. Example for run_attack: 'Returns a list of objects, each with fields: {vulnerability_id (string), severity (string: low|medium|high|critical), description (string), affected_model (string)}' or similar.
• Add parameter descriptions for model_name and probe_name in run_attack. Example: 'probe_name (string): Name of a Garak probe. Call list_garak_probes() first to see available options.'
• Add dry-run parameter to run_attack or document in description that calls are idempotent and can be safely retried. If not idempotent, explain side effects.
• Enhance descriptions with context and prerequisites. Example for list_models: 'List available models for a given type. Call this after list_model_types() to enumerate models you can use in run_attack.'
• Add error guidance to run_attack description: 'May fail if model_type is invalid, model_name does not exist, or probe_name is not found. If error occurs, call list_models() or list_garak_probes() to verify parameters.'
• Document get_report output: 'Returns the file path to the latest Garak report (JSONL format). If no report exists, returns empty string or null.'
• Add pagination/limit guidance to list_models and list_garak_probes if they can return large results. State expected result size and whether truncation is possible.