describe_table

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

With no annotations provided, the description carries the full burden and handles it well by disclosing caching behavior (5 minutes) and explaining how to handle Lookup fields with @odata.bind syntax. This adds valuable context beyond the basic fetch operation.

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 front-loaded with the core purpose and every sentence contributes meaning. It is somewhat lengthy due to the Lookup syntax explanation, but this detail is useful and not wasteful.

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 simple one-parameter tool with no output schema or annotations, the description covers the operation, usage context, key return contents, and caching. It could be more explicit about the overall response shape, but it is largely complete for agent use.

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 already fully documents the single parameter (tableName) with 100% coverage, and the description adds no additional parameter-level detail, meeting the baseline for acceptable schema coverage.

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 fetches the full metadata schema for a Dataverse table, specifying columns and relationship types. This distinguishes it from sibling tools like get_record (data retrieval) and list_tables (table listing).

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?

It explicitly instructs to ALWAYS call this before creating or updating records, providing strong contextual usage. However, it does not mention when not to use it or name alternatives, stopping short of a 5.

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