Server demonstrates solid fundamentals: all 7 tools have clear verb-noun names (list_, get_, set_), descriptions are present and contextual (avg ~120 chars), and input schemas are properly typed with required fields marked. Tool composition is clean, each tool has one responsibility. However, parameter descriptions are sparse or missing entirely (e.g., 'active' in list_workflows lacks description; 'limit' and 'sample' lack guidance on valid ranges). Output schemas are not formally documented, responses are inferred from code. Error handling is minimal; no recovery guidance or actionable error messages visible. The design philosophy ('read-only by default', 'answers not dumps') is excellent and evident in failing_workflows and health_summary, which aggregate server-side rather than dumping raw data. This is a B-grade server: good intent and structure, but parameter and error documentation gaps prevent higher scores.

• Add descriptions to all parameters. For 'limit' and 'sample', specify: 'Maximum number of items to return (1 - 250). Defaults to [X]. Larger values may slow queries.'
• Document output schemas formally. For each tool, add a 'returns' section in the docstring or a separate schema definition. Example: 'Returns {count: int, workflows: [{id, name, active, node_count, tags, updated_at}]}'.
• Add min/max constraints to numeric parameters. E.g., 'limit': {'type': 'integer', 'minimum': 1, 'maximum': 250, 'default': 100}.
• Implement error recovery guidance. Wrap API calls in try-except blocks that return structured errors: {'error': 'Workflow not found', 'suggestion': 'Call list_workflows() to see available IDs'}.
• Enhance set_workflow_active with a dry-run parameter or explicit confirmation requirement. E.g., add 'confirm: {type: boolean, description: "Must be true to activate/deactivate. Prevents accidental changes."}' as a required parameter.