dataverse_get_table_metadata

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

The description adds behavioral context beyond annotations: it specifies the returned attributes and explains the consistency_strong parameter's caching behavior and performance implications. This aligns with readOnlyHint, idempotentHint, and destructiveHint annotations without contradiction.

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 concise with four sentences, front-loaded with purpose. Every sentence adds value, including return values and prerequisite guidance. No wasted words.

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?

Given the output schema exists (implied by context), the description adequately covers the tool's purpose, return values, and parameter behavior. It is complete for a read-only metadata retrieval tool.

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?

The input schema fully describes all three parameters (table_name, dataverse_url, consistency_strong) with individual descriptions. The tool description does not add parameter-level meaning beyond the schema, so baseline score of 3 applies.

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 tool retrieves schema details for a single Dataverse table by logical name, specifying the return values (entity set name, primary key, primary name attribute). This distinguishes it from sibling tools like dataverse_list_tables which list available tables.

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 instructs users to use dataverse_list_tables to discover table logical names, providing a clear prerequisite. However, it lacks explicit guidance on when not to use this tool or direct comparison with other get_* tools.

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