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

Annotations already declare the tool as read-only and idempotent. The description adds valuable behavioral context by specifying that the result is expressed as a positive percent, and it explains the calculation method (peak-to-trough), which goes beyond 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?

One sentence that front-loads the purpose and then defines the term. No redundant information or filler, making it highly concise and well-structured.

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 simple one-parameter input, the presence of an output schema, and annotations covering safety, the description adequately covers the tool's behavior. It defines the metric sufficiently for an agent to select and invoke the tool correctly.

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 coverage is 100%, and the single parameter 'series' is already described as 'Sequence of values (e.g. portfolio levels).' The description repeats the same concept without adding new semantics, so the baseline score of 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 computes maximum drawdown of a value series, defining it as the largest peak-to-trough decline. The verb 'compute' is implicit in the definition, and the scope distinguishes it from sibling metrics like return-stats or cagr.

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 makes the usage context clear: it is for a value series, such as portfolio levels. It does not explicitly exclude alternatives or compare with sibling tools, but the uniqueness of the metric is obvious from the definition.

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