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

Annotations already declare readOnlyHint=true, destructiveHint=false and closed-world, so the safety profile is covered. The description adds genuinely new behavioral facts: the aggregation is bounded and database-side, SQL and tenant IDs are rejected, and the response echoes the applied measure definitions.

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?

Two dense sentences, the operation list front-loaded and the two hard constraints (no SQL, no tenant ID) placed last where they are easy to scan. The operation enumeration is long but each term maps to real capability, so little is wasted.

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?

An output schema exists, so return values need no prose explanation. But for a 7-parameter tool with 0% schema coverage and required source/table/measures, the description leaves the required-parameter contract and the structure of filters/dateBuckets/measures largely undocumented, which is a real gap for correct invocation.

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?

With 0% schema description coverage on 7 parameters, the description carries the load: it names the measure operations that populate `operation`, and references grouping, date buckets, and structured filters, which maps to groupBy, dateBuckets and filters. However it says nothing about `source`, `table`, `limit`, the direction/percentile options, or the shape of a filter object, so the compensation is partial.

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?

States a specific verb (aggregate/run measures) plus the full taxonomy of supported operations (count, distinct count, sum, percentile, rank, running-sum) and the two axes of scoping (grouping/date buckets, filters). The explicit 'Never accepts SQL' also separates it from the query_table sibling without the agent needing to open either schema.

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 constraints ('bounded', 'never accepts SQL or a tenant ID') implicitly steer the agent here for aggregated metrics rather than raw row retrieval, but no sibling is named and there is no explicit when-to-use/when-not statement relative to query_table or describe_table. Usage is inferable rather than stated.

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