tokscale_breakdown

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

The annotations already include readOnlyHint=true, so the description does not need to state that this is a read operation. The description adds context about the lumping behavior and the return format, but no additional behavioral traits beyond what annotations already provide.

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 two sentences plus an example and return structure. It is concise, front-loaded, and every sentence adds value. No wasted words or redundancies.

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 description covers the tool's purpose, parameter, example usage, and return format. It is adequate given the presence of annotations and output schema. A slight improvement could be mentioning that this is a read-only operation, but that is already covered by annotations.

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%, so baseline is 3. The description adds meaning by explaining the threshold's effect (lumping models below threshold into 'other') and giving an example, which goes beyond the schema's description of 'fraction of their platform's total tokens'.

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 verb ('Show'), the resource ('per-model breakdown of your token usage'), and the scope ('across all platforms detected by tokscale'). It effectively distinguishes this tool from siblings by specifying the model-level breakdown, which is unique among the listed siblings.

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 explains when to use this tool: to see which models you actually use per platform. It provides guidance on the threshold parameter and its default behavior, but does not explicitly mention when not to use it or suggest alternatives.

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