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Get Config Value

config_get
Read-only

Retrieve a specific configuration setting from a Cloudeval CLI profile by supplying the config key. Resolve the value from profile, environment, or API defaults.

Instructions

Return one setting from the selected Cloudeval CLI profile.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesConfig key.
baseUrlNoCloudeval API base URL. Defaults to the MCP server --base-url, active profile, CLOUDEVAL_BASE_URL, or the public API.
profileNoCloudeval CLI config profile to read defaults from. Defaults to the server --profile or CLOUDEVAL_PROFILE.
frontendUrlNoCloudeval frontend base URL for generated links. Defaults to --frontend-url, active profile, CLOUDEVAL_FRONTEND_URL, or public frontend.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYes
dataYesTool-specific result payload.
commandYes
traceIdNo
frontendUrlNo
filesWrittenNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.38.3

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds the source context ('selected Cloudeval CLI profile') but does not disclose fallback behavior, local-vs-remote semantics, or error handling. Minimal additional behavioral context beyond the annotations.

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 a single concise sentence that front-loads the core action and result. There is no filler or redundant content, making it easy for an agent to parse quickly.

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 read-only config getter, the description, combined with fully described schema parameters, annotations, and an output schema, provides enough to invoke the tool correctly. The main gap is the lack of explicit differentiation from config_show, but this is a minor omission given the overall simplicity.

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 the baseline is 3. The description does not add meaningful parameter semantics beyond the schema; the 'one setting' wording loosely maps to the key parameter but provides no new detail. The schema descriptions already explain defaults and precedence.

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 action ('Return') and the resource ('one setting from the selected Cloudeval CLI profile'). The phrase 'one setting' helps distinguish it from sibling tools like config_show, though it does not explicitly name alternatives. It is specific enough for an agent to understand the core operation.

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 implies a single-setting lookup use case but provides no explicit guidance about when to use this tool over siblings like config_show or config_profiles. There are no exclusions or alternative suggestions, so the agent must infer routing from the tool name and context.

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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