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get-usages

Retrieve usage analytics including compute units consumed and assets generated, with filtering by user, project, time range, and activity type.

Instructions

Provide usage data for the given filters. Such as consumed compute units, number of assets generated, etc. Maximum time range with custom startDate and endDate is 120 days. Granularity is calculated based on the time range.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
userIdNoThe unique identifier of the user for the usage. If not provided, returns all usages for the team.
activityOffsetNoThe offset for the activity data. Default is 0. If bad offset or empty, 0 will be returned. Must be a positive integer.
userIdsNoThe unique identifiers of the users for filtering the usage data. If not provided, use all users. Can be one or more comma separated values.
typeNoThe type of the usage data. Can be one or more comma separated values. Default is all types. If bad type or empty, all types will be returned.
endDateNoThe end date of the usage in ISO 8601 format. If not provided, use default timeRange. If provided, startDate is required.
projectIdsNoThe project ids for filtering the usage data. If not provided, use all projects. Can be one or more comma separated values.
timeRangeNoThe time range of the usage. If not provided, use default timeRange. If startDate and endDate provided, timeRange is ignored.
startDateNoThe start date of the usage in ISO 8601 format. If not provided, use default timeRange. If provided, endDate is required.
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context about time range limits and granularity calculation, which aren't in the schema. However, it doesn't cover other important aspects like response format, pagination, error handling, or rate limits, which are critical for a tool with 8 parameters and no output schema.

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

Conciseness4/5

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

The description is concise and front-loaded, with the first sentence stating the core purpose and examples. The second sentence adds necessary constraints without redundancy. Both sentences earn their place by providing distinct information, though it could be slightly more structured for clarity.

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 the tool's complexity (8 parameters, no annotations, no output schema), the description is moderately complete. It covers the purpose and some behavioral constraints but lacks details on output format, error cases, and full usage scenarios. This leaves gaps that could hinder an agent's ability to use the tool effectively without trial and error.

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 schema description coverage is 100%, so all parameters are documented in the schema itself. The description adds minimal value beyond the schema by implying filtering capabilities and time range constraints, but it doesn't provide additional syntax, format details, or examples. This meets the baseline for high schema coverage.

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's purpose: 'Provide usage data for the given filters. Such as consumed compute units, number of assets generated, etc.' It specifies the verb ('provide') and resource ('usage data') with concrete examples, making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like other 'get-' tools (e.g., get-assets, get-models), which prevents a perfect score.

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

Usage Guidelines3/5

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

The description provides some implied usage context by mentioning time range constraints ('Maximum time range... is 120 days') and granularity calculation, which helps set expectations. However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., other data retrieval tools) or any prerequisites, leaving gaps in optimal usage scenarios.

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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