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DoiT MCP Server

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by doitintl

get_dimension

Read-only

Retrieve valid filter values for a specific dimension to configure accurate cost queries, or view dimension details.

Instructions

Use this to look up the valid filter values for a specific dimension before calling run_query — for example, call get_dimension({type: 'fixed', id: 'cloud_provider'}) to get the exact provider IDs available for this customer. Also use this when the user wants to view dimension details. Do NOT use this for listing all dimensions (use list_dimensions) or running queries (use run_query).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesDimension type
idYesDimension id
Behavior4/5

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

Annotations already declare read-only; description adds that values are customer-specific and filter-oriented. No contradictions.

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?

Three sentences: main purpose, example, negation. No fluff, front-loaded.

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?

For a simple lookup tool, purpose, usage, and exclusions are well covered. Missing explicit return format, but not critical given purpose.

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

Parameters4/5

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

Schema covers both params with descriptions; description adds an example mapping type and id to realistic values, slightly enhancing meaning.

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?

Clearly states verb 'look up valid filter values' for a specific dimension and distinguishes from siblings list_dimensions and run_query.

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

Usage Guidelines5/5

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

Explicitly tells when to use (before run_query, view dimension details) and when not (list_dimensions, run_query), with a concrete example.

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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