get_usage

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 discloses meaningful behavioral details: specific time windows (5-hour, 7-day), per-model limits, output format (utilization percentages), and reset timestamps. It does not explicitly state read-only behavior, but 'Report' strongly implies a non-mutating operation.

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 well-structured sentence that front-loads the core purpose and then packs in the key details: time windows, per-model limits, and output format. There is no wasted text.

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 parameterless read-only reporting tool, the description is largely complete. It specifies the scope, the metrics, the format, and reset timestamps. Some minor ambiguity remains about the exact response structure, but no output schema exists and the description provides sufficient practical detail for an agent to 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?

The tool has zero parameters, so the baseline is 4. The description adds useful context about what kind of usage data is returned, but there are no parameter semantics to clarify since none exist.

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 specific verb 'Report' and the exact resource 'the current user's Claude subscription usage', then enumerates the precise metrics covered: session window, weekly limit, and per-model limits. This is unambiguous and sufficiently detailed for an agent to understand what the tool does.

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 clearly implies this tool should be used when an agent needs to check the current user's Claude subscription usage or limits. There are no siblings to differentiate against, and no exclusion criteria are stated, but the context is clear enough for straightforward invocation.

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