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

Annotations already cover the read-only and idempotent nature, so the description adds the valuable behavioral constraint that the listed column names are the only ones the query grammar accepts, plus the immutability of version_id. This goes beyond what annotations alone convey.

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?

Three sentences accomplish a lot: they enumerate the return contents, provide a concrete example, and give a critical usage rule. There is no redundancy, and the most actionable warning is placed at the end where it stands out.

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 read-only, single-parameter tool, the description thoroughly covers what is returned, the parameter example, and the critical interaction with query_table. Minor omissions like response format or error behavior are acceptable given the simplicity and annotations.

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?

There is only one parameter and the schema description coverage is 0%, so the description carries the full burden. It supplies a concrete UUID example and contextualizes the table, but it never explicitly defines table_id as the table identifier, leaving some meaning implicit in the title and example.

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 specifies the resource (one table) and the exact output shape (columns with type/profile and capabilities), and it calls out the query_table sibling by name, making the tool's role unambiguous.

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 gives a concrete, actionable usage instruction—'Read this before writing a query_table call'—which is a strong when-to-use signal. It does not enumerate other sibling alternatives, but it effectively coordinates with the most relevant one.

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