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

With no annotations, the description carries the burden of behavioral disclosure. It is clear that the tool likely updates internal state (tracking calibration) and performs analysis, but it does not specify if it mutates state, requires permissions, or the specifics of its output. It is somewhat transparent but lacks depth on behavioral side effects.

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 concise—a single sentence that front-loads the core purpose. It is not verbose or redundant, and the key action is immediate. However, it could benefit from a brief elaboration on calibration tracking, but it remains efficient.

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?

The tool is conceptually complex (classifying task types and tracking calibration), and the output schema exists, so return format may be covered. However, the description lacks crucial context: what types of inputs are expected, what the tool returns (though output schema may help), and how it interacts with other tools. The absence of parameter explanations and usage guidance leaves significant gaps.

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 0%, so the schema provides no explanations for `task_structure` or `actual_outcome`. The description does not elaborate on these parameters either, only mentioning 'task' generically. This is a significant gap given both parameters are undocumented, and the description fails to compensate.

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 identifies the tool's purpose: classifying tasks into epistemic categories (KNOWN, KNOWN_UNKNOWN, UNKNOWN_UNKNOWN) and tracking calibration. It uses specific verbs and a clear resource ('task') and provides a distinct functionality from siblings, though it doesn't explicitly name alternatives.

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 no explicit guidance on when to use this tool versus alternatives. It implies it is for assessing competence and epistemic awareness, but does not mention conditions, exclusions, or alternative tools. An agent would have to infer usage from the name and description alone.

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