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usage

Retrieve usage records with billing details for workspace endpoints. Includes time series data and summary statistics with quantities and prices.

Instructions

Get usage records for workspace with detailed billing information. Returns time series data and/or summary statistics with unit quantities and prices. Requires authentication.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endpoint_idsYesEndpoint ID(s) to get usage for (e.g., ['fal-ai/flux/dev']). Must provide at least 1 endpoint ID (1-50 models).
startNoStart date in ISO8601 format (e.g., '2025-01-01T00:00:00Z' or '2025-01-01'). Defaults to 24 hours ago.
endNoEnd date in ISO8601 format (e.g., '2025-01-31T23:59:59Z' or '2025-01-31'). Defaults to current time.
timezoneNoTimezone for date aggregation (e.g., 'UTC', 'America/New_York'). Defaults to 'UTC'.UTC
timeframeNoAggregation timeframe for timeseries data. Auto-detected from date range if not specified.
bound_to_timeframeNoWhether to align start/end dates to timeframe boundaries. Defaults to true.
expandNoData to include: 'time_series' for time-bucketed data, 'summary' for aggregates, 'auth_method' for auth tracking. Defaults to ['time_series'].
cursorNoPagination cursor from previous response.
limitNoMaximum number of items to return.
Behavior2/5

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

With no annotations provided, the description carries full burden. It only notes authentication requirement. There is no mention of rate limits, idempotency, pagination behavior, or data freshness. The return types are described but not in detail.

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?

The description is two sentences and contains only essential information. It starts with the action and resource, then adds key return details. No redundant or irrelevant text.

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 no output schema, the description should explain return values more thoroughly. It mentions time series and summary statistics but lacks specifics on structure or pagination. For a tool with 9 parameters, this is adequate but not comprehensive.

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?

Schema description coverage is 100%, so baseline is 3. The description adds no additional meaning beyond what the schema already provides for parameters like 'endpoint_ids' or 'expand'. It does not explain parameter interactions or edge cases.

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

Purpose5/5

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

The description clearly states the tool retrieves usage records with billing information, specifying verb 'Get', resource 'usage records', and additional context about time series and summary data. This distinctly communicates the tool's function and differentiates it from siblings like 'pricing' or 'analytics'.

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?

The description provides no guidance on when to use this tool versus alternatives such as 'analytics' or 'pricing'. It does not mention any prerequisites, exclusions, or scenarios where this tool is preferred, leaving the agent without decision support.

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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