usage_report

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

No annotations are provided, so the description carries full burden. It discloses that the report is real and returns specific breakdowns, but lacks details on prerequisites (e.g., file system access), potential side effects, input validation, or error conditions. It adequately describes outputs but omits operational context.

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 with no filler. The first sentence concisely states the action and source, the second lists outputs. Every word earns its place.

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 no output schema, the description partially explains return values (breakdowns, burn rates) but does not specify the format or structure. For a tool generating a detailed report, this leaves some gaps in completeness.

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% with a clear description for the 'days' parameter. The description adds no new semantic information beyond what the schema already provides, so it meets the baseline but does not exceed.

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 generates a real (not estimated) token usage and cost report from Claude Code's JSONL records, with specific breakdowns per model, project, and day, plus burn rates and projected spend. It uses a specific verb and resource, distinguishing it from siblings like estimate_cost.

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 implies when to use (for real data rather than estimated) but does not explicitly name alternatives or provide exclusions. Siblings usage_analytics and estimate_cost are present but not referenced, leaving some ambiguity.

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