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usage_summary

Retrieve total requests, tokens, and cost from LLM usage. Optionally break down by provider, model, project, hour, or day.

Instructions

Get cost/usage summary. Returns total requests, tokens, cost, with optional breakdown by provider, model, project, hour, or day.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoEnd date (ISO format, e.g. "2026-03-23")
fromNoStart date (ISO format, e.g. "2026-03-01")
modelNoFilter by model
groupByNoGroup breakdown by: "provider", "model", "project", "hour", "day"
projectNoFilter by project
providerNoFilter by provider
Behavior2/5

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

With no annotations, the description carries the full burden. It fails to disclose whether the tool is read-only, any rate limits, required authentication, or side effects. It only describes the output metrics, not operational behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single, well-structured sentence that conveys the core purpose and optional breakdowns. No unnecessary words or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 6 optional parameters and no output schema, the description could explain default date ranges, behavior when no filters are set, and the output format. It covers the basics but leaves gaps for an agent to infer.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds context that the tool returns total requests, tokens, and cost, mapping to the parameters. However, schema coverage is 100%, so added value is moderate; the description does not introduce new semantics beyond reinforcing the breakdown options.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves a cost/usage summary including requests, tokens, cost, and optional breakdowns. It distinguishes from vague or unrelated tools, but could be more explicit about its relation to similar tools like usage_query.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives such as usage_query. The description does not mention prerequisites, default behavior, or scenarios where one tool is preferred.

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

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