median

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 explains what the median is ('middle value... separates higher half from lower half'), but lacks critical behavioral details: how it handles empty lists, even vs. odd list lengths, non-numeric inputs, or error conditions. For a tool with no annotation coverage, this is a significant gap in transparency.

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 appropriately concise and front-loaded: the first sentence directly states the purpose, and the second adds clarifying definition. The parenthetical domain/category note is brief and relevant. There is no wasted verbiage, making it efficient for an agent to parse.

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 simplicity (one parameter, no annotations, no output schema), the description is incomplete. It lacks details on parameter handling, edge cases (e.g., empty arrays, even-length lists), and expected output format. While the purpose is clear, the absence of behavioral and parametric context makes it insufficient for reliable agent use.

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 0% description coverage, with one parameter 'numbers' of type array of strings. The description does not compensate by explaining parameter semantics: it doesn't clarify that 'numbers' should be numeric strings, specify format (e.g., integers, floats), mention handling of invalid entries, or note that the array must be non-empty. This leaves the parameter poorly documented.

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 purpose: 'Calculate the median (middle value) of a list of numbers.' It specifies the verb ('calculate') and resource ('median'), and distinguishes it from siblings by mentioning its statistical domain. However, it doesn't explicitly differentiate from similar statistical tools like 'mean' or 'mode' in the sibling list, which would require 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 provides no guidance on when to use this tool versus alternatives. It mentions the domain (statistics) and category (general), but offers no explicit when/when-not instructions or references to sibling tools like 'mean' or 'quartiles' for comparison. This leaves the agent without practical usage context.

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