Server has 29 tools with consistent naming (verb_noun pattern) and basic schemas. Most tools have descriptions (10-50 chars, below the 50-200 char baseline for LLM optimization). Input schemas are present but lack depth: parameters have types and brief descriptions, but many lack constraints (enums, ranges, patterns). Output schemas are not documented. Error handling is minimal, no recovery guidance or actionable error messages visible. Validation logic exists (validateWorkflowDefinition) but is not exposed as a tool. Composition is reasonable (tools are single-purpose), but critical gaps in parameter constraints and output documentation prevent higher scores.

• Expand tool descriptions to 50-200 characters. Include WHAT the tool does, WHEN to use it, and any prerequisites. E.g., 'List all workflows with optional filtering by active status, tags, or name. Returns paginated results (default limit 20). Use this to discover workflows before executing or updating them.'
• Document output schemas for all tools. Specify returned fields, types, and which IDs are needed for chaining. E.g., list_workflows should return [{workflowId, name, active, tags, createdAt}] so agents can pass workflowId to get_workflow or execute_workflow.
• Add enum constraints to parameters with known valid values. E.g., status in list_executions should be enum: ['success', 'error', 'running', 'waiting']. Use get_node_types to discover valid node categories and declare them as enums.
• Implement error recovery guidance. When a workflow is not found, return 'Workflow not found. Try list_workflows() to find the correct ID.' When validation fails, return specific field errors with suggestions.
• Add a confirm_delete_workflow tool or require a confirmation parameter (e.g., confirmed: true) for delete_workflow and delete_execution. Alternatively, implement a dry-run mode that shows what would be deleted without executing.

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

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