list_stats

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

Annotations are absent, so the description carries the transparency burden. It conveys a read-only listing operation with no side effects, but does not disclose pagination, response format, or authorization requirements. The 'call this first' guidance adds useful context, but behavioral depth is limited.

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, front-loaded sentence with no wasted words. It states the action, scope, and usage guidance efficiently.

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?

For a simple one-parameter tool with no output schema, the description covers purpose, usage, and basic output (names and types). It lacks an explicit return structure or pagination details, but these are not critical for a discovery tool.

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% for the single parameter 'type', with a detailed description including enum meanings. The tool description adds no additional parameter semantics, so the baseline 3 applies when the schema already does the heavy lifting.

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?

Description clearly states the verb 'List', the resource ('the account's metrics'), and the output content ('names and types'). The added instruction 'Call this first when you don't know what stats exist' further distinguishes it from sibling tools like read_stat or track_metric, positioning it as the discovery tool.

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?

Explicit guidance is given: 'Call this first when you don't know what stats exist in the account.' This provides a clear when-to-use. It does not explicitly name alternatives or when-not-to-use, but the scoping to names/types implies other tools are for values or tracking.

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