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Search Rules

rules_search
Read-only

Search cloud validation checks by query, architecture pillar, or category to pinpoint compliance and design issues in Azure and AWS environments.

Instructions

Search cloud validation checks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query.
pillarNoArchitecture pillar filter.
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.
categoryNoCategory filter.
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

B3.1/5.0
Behavior2/5

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

The annotations already disclose readOnlyHint=true, openWorldHint=true, and destructiveHint=false, and the description adds no behavioral context beyond the bare search action. It does not contradict the annotations, but it also provides no extra detail about result scoping, pagination, or other runtime behavior.

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 front-loaded sentence with no filler, repetition, or unnecessary detail. It earns its place by stating the core action and resource immediately.

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 the schema is well documented, an output schema exists, and annotations cover the safety profile, the description is minimally adequate. However, it omits what makes this search distinct from sibling rule/report tools and does not explain the scope of 'cloud validation checks,' leaving an agent to infer context.

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?

The input schema has full (100%) coverage with descriptions for all six parameters, so the baseline is 3. The main description only clarifies that the query targets cloud validation checks; it does not add meaningful semantics beyond the schema.

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 uses a specific verb ('Search') and a concrete resource ('cloud validation checks'), so an agent can tell it is a read-oriented lookup tool. It does not explicitly contrast with sibling tools like rules_get or rules_categories, so it stops short of full sibling differentiation.

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?

There is no guidance about when to use this tool versus sibling tools such as rules_get, rules_categories, or reports_rules. The word 'Search' implies a broad query use case, but no alternatives, exclusions, or conditions are stated.

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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