Five tools with clear verb-noun naming and consistent READ_ONLY annotations. All tools have descriptions (10 - 200 chars) and input schemas with types. However, parameter descriptions are sparse or missing entirely (e.g., 'category' in list_workflows lacks guidance on what metadata it filters; 'provider' in render_provider_asset has no description). Output schemas are not documented, LLMs cannot infer what fields to expect from responses. Error handling delegates to service.structured_call() but no recovery guidance is visible. Tool composition is sound (each does one thing), but descriptions fall short of LLM-optimized length (50 - 200 chars baseline). Baseline: avg param description 72 chars; 100% of A+ tools have param descriptions, this server has ~40% coverage.

• Add parameter descriptions to all inputs. E.g., 'category: Case-insensitive substring match against workflow name, title, description, and commands. Useful for filtering by domain (e.g., "testing", "deployment").'
• Document output schemas in tool descriptions or as structured comments. E.g., 'Returns {workflows: [{name, title, description, commands}], count: int, total: int}'.
• Expand tool descriptions to 100 - 200 chars. Include WHEN to use: 'List workflows to discover available automation patterns. Use category to filter by domain. Call before get_workflow to find the right workflow name.'
• Add constraint guidance to parameter descriptions. E.g., 'max_chars: Maximum characters in response (1000 - 50000, default 20000). Increase for large workflows; decrease to save tokens.'
• Document error codes and recovery paths in service.py. E.g., 'WorkflowServerError("workflow-not-found") → suggest calling list_workflows() to find valid names.'