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

With no annotations, the description carries the full burden. It adds useful behavioral context by stating the output range (0-25) and the three input components, which covers the core behavior of a pure computation tool. However, it does not explain how the score is derived, what higher scores mean, or how missing/edge-case inputs are handled.

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 a single, front-loaded sentence with no filler. It states the output metric, its range, and the relevant inputs efficiently, earning its place for a simple compute tool.

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 lightweight compute tool, the description provides the essential output range and input list, and there is no output schema to explain return values. But it lacks guidance on which sibling variant to use, how the score is calculated, and edge-case behavior, leaving an agent to guess at key selection and invocation details.

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?

Schema description coverage is only 33%, so the description must compensate, but it mostly restates the parameter names. It adds 'Trends' context for timelineValues but gives no extra semantics for risingQueriesCount or geoRegionCount beyond what their names already imply, and no guidance on defaults, ranges, or relative weighting.

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 identifies a specific computation ('Compute search_velocity_score') and its input components, which makes the tool's purpose clear. However, it does not differentiate this from compute_search_velocity_v2 or the many other compute_* siblings, so it misses the distinction criterion for a 5.

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 implies the tool is used to compute a search velocity score, but it gives no guidance on when to choose this over compute_search_velocity_v2 or any other alternative. There are no exclusions, prerequisites, or context signals.

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