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get_cluster_costs

Retrieve aggregated cost breakdown for an Ocean cluster on AWS or Azure. Group costs by namespace for a specified time period to analyze spending.

Instructions

Get aggregated cost breakdown for an Ocean cluster (AWS or Azure).

Args: cluster_id: The Ocean cluster ID (e.g. o-abc12345) start_time: Start time in ISO 8601 format (e.g. 2026-03-01T00:00:00Z) end_time: End time in ISO 8601 format (e.g. 2026-03-20T00:00:00Z) group_by: Group costs by: namespace (default: namespace). Only 'namespace' is currently supported by the API. account_id: Optional account ID to query. Defaults to SPOTINST_ACCOUNT_ID env var. cloud: Cloud provider: aws or azure (default: aws) limit: Max namespace aggregations to return, sorted by cost descending (default: 50). Set limit=0 for all.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cluster_idYes
start_timeYes
end_timeYes
group_byNonamespace
account_idNo
cloudNoaws
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Despite no annotations, the description discloses important behaviors: aggregation by namespace, sorting by cost descending, limit behavior, and that only 'namespace' is supported for group_by. This helps the agent understand side effects and constraints.

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 uses a clear 'Args' list structure but is somewhat long. It front-loads the purpose then details parameters. Every sentence provides value, though some parameter explanations could be more concise.

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

Completeness5/5

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

Given the output schema exists, the description need not explain return values. It covers all seven parameters, their defaults, and special behaviors (e.g., limit=0). For a tool with this complexity, the description is fully sufficient.

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

Parameters5/5

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

Schema coverage is 0%, but the description fully documents each parameter with examples, defaults, allowed values (e.g., cloud: 'aws or azure'), and behavioral notes (e.g., group_by only supports 'namespace', limit=0 returns all). This adds significant value beyond the schema.

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 'Get aggregated cost breakdown for an Ocean cluster (AWS or Azure).' It specifies the resource (Ocean cluster), action (get aggregated cost breakdown), and cloud support, distinguishing it from sibling tools like get_cluster or get_cost_trending.

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 parameter details and implies usage (e.g., when needing cost breakdown by namespace for a specific cluster), but lacks explicit guidance on when to use this tool versus alternatives like get_cost_trending or when not to use it.

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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