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alexpota

cloudscope-mcp

Cloud Cost Summary

get_cost_summary
Read-onlyIdempotent

Return a cloud cost breakdown grouped by service, resource group, tag, or region for a specified date range. Includes total cost, daily average, and collapses small groups into an 'Other' row.

Instructions

Returns a cost breakdown for a date range grouped by service, resource group, tag, or region. Defaults to current month if dates are omitted. Output includes a sorted table with each group name, cost in USD, and percentage of total. Includes a total row, daily average, and collapses groups beyond the top 10 into an "Other" row. Returns an error if the date range is invalid. Use this when the user asks "how much am I spending", "what costs the most", "show me my cloud bill", or wants a spending overview.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
providerNoCloud provider to query (azure or gcp)azure
start_dateNoStart date (YYYY-MM-DD). Defaults to first of current month.
end_dateNoEnd date (YYYY-MM-DD). Defaults to today.
group_byNoHow to group costs: service, resource_group, tag, or regionservice
Behavior4/5

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

The description adds details beyond the annotations: it explains the output format (sorted table with percentage, total row, daily average, and 'Other' row for groups beyond top 10), and mentions error behavior for invalid date ranges. This complements the readOnlyHint and idempotentHint well.

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 four sentences, each serving a purpose: first defines the function, second explains defaults, third details output, fourth warns about errors and gives usage examples. It is well-structured and not overly long.

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

Completeness4/5

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

Given no output schema, the description compensates by detailing the output structure. It covers all four parameters implicitly and addresses common use cases. For a read-only summary tool with 15 siblings, it provides enough context to distinguish from related tools like get_cost_by_tag or compare_periods.

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 coverage is 100% with descriptions for all parameters. The description does not add new semantics beyond defaults (e.g., provider defaults to azure, dates default to current month/today) which are already in the schema. So minimally adds value.

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 it returns a cost breakdown grouped by service, resource group, tag, or region for a date range. It gives specific example queries like 'how much am I spending' and 'show me my cloud bill', which makes the purpose immediate and distinguishable from siblings.

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

Usage Guidelines4/5

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

The description explicitly says to use this tool when the user asks for cost overviews, providing concrete query examples. However, it does not mention when to avoid it or suggest alternatives like get_cost_by_tag for specific tag breakdowns, which would make it more complete.

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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