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

Annotations already cover readOnly, idempotent, and non-destructive behavior, so the description only needs to add context around the data access. It adds that the tool returns saved, account-scoped metric definitions rather than live computations, which is useful and does not contradict the annotations.

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 three sentences long, starts with the core action, and uses examples and backticked field names efficiently. It is slightly dense with domain terminology, but every sentence contributes to understanding what is listed and what to do next.

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 zero-parameter list tool with no output schema, the description does a good job of explaining the returned metric structure and the relationship to query_unit_costs. It could more explicitly state the output shape (e.g., an array of metric definitions), but the current text is sufficient for correct invocation and interpretation.

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 has zero parameters, so the baseline is 4. The description adds meaningful context by explaining the fields of the returned metrics — numerator_scope, denominator_metric, denominator_scale — and pointing out that an id feeds into query_unit_costs. This helps an agent interpret results, even though these are not input parameters.

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 opens with a specific verb and resource — 'List this account's saved unit-economics metrics' — and immediately defines what those metrics are with concrete examples. It also distinguishes itself from the sibling query_unit_costs by noting that an id would be passed there for computation.

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 gives a clear pointer to query_unit_costs for computing a metric over a date range, which implies the intended division of labor. It does not explicitly state exclusions or exhaustive when-to-use guidance, but the context is clear enough for an agent to pick the right tool.

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