MCP Server for OpenMetadata

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a read operation ('Get details'), which implies it's non-destructive, but doesn't address authentication requirements, rate limits, error responses, or what 'details' actually includes. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the essential information. There's zero wasted verbiage or redundancy, making it immediately scannable and understandable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 2 parameters, 0% schema coverage, no annotations, and no output schema, the description is inadequate. It doesn't explain what 'details' are returned, doesn't document the optional 'fields' parameter, and provides no behavioral context. The agent would struggle to use this tool effectively without additional documentation or trial-and-error.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the schema provides no parameter documentation. The description mentions 'fully qualified name' which corresponds to the 'fqn' parameter, but doesn't explain what constitutes a valid FQN or provide examples. It completely ignores the 'fields' parameter, leaving half the parameters undocumented. The description adds minimal value beyond what's implied by parameter names.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Get details') and target resource ('specific ML model by fully qualified name'), making the purpose immediately understandable. However, it doesn't explicitly distinguish this from sibling tools like 'get_ml_model' (which presumably retrieves ML models by ID rather than name), so it misses the highest score for sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'get_ml_model' or 'list_ml_models'. It doesn't mention prerequisites, error conditions, or typical use cases, leaving the agent to infer usage from the tool name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.