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

No annotations are provided, so the description carries the full burden. It discloses that the tool computes the listed statistics and implicitly that it does not modify the input, but it does not explain how missing or non-numeric values are handled, nor the exact return format. For a read-only computation, this is acceptable but leaves gaps.

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, concise sentence that front-loads the action and includes the essential detail of which statistics are computed. Every word earns its place, with no redundancy or filler.

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?

Given the tool's low complexity (two required parameters, no output schema, no annotations), the description covers the core functionality well: computing specific stats on a numeric field. It lacks edge-case handling and explicit return details, but for a simple computation tool, this is largely sufficient. Sibling tool differentiation is not explicitly addressed, but the purpose clarity resolves this.

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 provides full descriptions for both parameters ('data' as array of objects, 'field' as numeric field). The description does not add parameter-specific meaning beyond what the schema states; it only clarifies the output statistics, which is not parameter-level. With 100% schema coverage, baseline 3 is appropriate.

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's action ('Compute') and the resource ('statistics for a numeric field'), listing specific statistics (count, sum, mean, min, max, median). This distinguishes it from sibling tools like filter, sort, or flatten, which perform different transformations.

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 when to use the tool (when needing statistical aggregations on a numeric field), but it does not explicitly state when not to use it or mention alternatives. There is no comparison to sibling tools, so the agent must infer usage from the tool name and description.

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