get_usage_report

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

With no annotations provided, the description carries the full disclosure burden. It does disclose the return behavior ('Returns totals and breakdowns by agent and model') and implies a side-effect-free read operation. It omits details like data freshness, empty-result behavior, or permission requirements, but the core behavioral profile of a simple aggregation query is conveyed.

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?

Two sentences with zero filler: the first front-loads the action and scope, the second states the return value. Every clause earns its place, and there is no repetition of schema content.

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 tool with 5 optional parameters, no annotations, and no output schema, the description covers the core invocation semantics: what it aggregates and what it returns. Gaps remain around the default time range when dates are omitted, whether breakdowns are always by both agent and model, and the response format — but these do not block a basic correct invocation.

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 100%, so each of the 5 parameters is already documented in the schema, warranting the baseline 3. The description adds mild connective meaning by naming 'tasks, agents, projects, and time ranges' as aggregation dimensions, which maps to the task_id/agent_id/project_id/from_date/to_date filters, but it does not explain interdependencies or defaults.

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 uses a specific verb ('Aggregate') with a clear resource ('token and cost usage'), then specifies the scope ('across tasks, agents, projects, and time ranges') and the return shape ('totals and breakdowns by agent and model'). This clearly positions it as the query/report counterpart to sibling log_usage, so an agent can distinguish them without opening schemas.

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 reporting use case is implied through the aggregation language, and the contrast with sibling log_usage (which records usage) is inferable. However, the description never explicitly states when to use this tool versus alternatives, nor any conditions or exclusions.

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