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Test Smart Mock

test_smart_mock
Read-only

Test smart mock matching for any field name to see which rule applies and what value it will generate. Verify your mock configuration before generating rules.

Instructions

Test Smart Mock matching for a given field name. Returns which matching rule would apply and what value it would generate. Useful for verifying Smart Mock configuration before generating rules. Requires project context (call set_context first).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldNameYesThe field name to test matching for (e.g., 'email', 'firstName', 'createdAt')
schemaTypeNoOptional JSON Schema type hint (e.g., 'string', 'integer', 'number', 'boolean')
mockServerIdYesThe public Id (Guid) of the mock server
schemaFormatNoOptional JSON Schema format hint (e.g., 'date-time', 'email', 'uri', 'uuid')

Schema Changelog

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

  1. First observedv1.1.1

TDQS

A4/5.0
Behavior4/5

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

The readOnlyHint annotation already signals a safe read operation. The description adds useful state-dependent context: it requires project context and explains the output conceptually (which matching rule applies and what value would be generated). This goes beyond the annotation without contradicting it.

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 short sentences, each carrying distinct value: what the tool does, what it returns, and when/how to use it. No redundant phrasing or filler. The most important action is 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 read-only testing tool with complete parameter schema coverage, this description covers the purpose, output behavior, and prerequisite state. It does not mention edge cases like no matching rule or error responses, but those are not critical for an agent to invoke the tool correctly.

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 schema already documents all four parameters well. The description adds only general context around 'field name' and does not explain parameter relationships or formats, so it meets the baseline but does not exceed it.

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 verb and resource: testing Smart Mock matching for a given field name, and explains what it returns. It is specific enough to distinguish from most sibling list/get tools, though it does not explicitly differentiate itself from the closely named 'preview_smart_mock' sibling.

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 gives a clear use case ('verifying Smart Mock configuration before generating rules') and a required prerequisite ('call set_context first'). It lacks explicit when-not-to-use guidance or named alternatives, so it stops short of a perfect usage-route score.

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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