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List Smart Mock Matching Rules

list_smart_mock_matching_rules
Read-only

List the Smart Mock matching rules of one mock server — the rules that decide which faker value a field name gets. Includes the built-in catalog unless you filter it out. Requires project context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skipNoNumber of rules to skip (for pagination, default 0)
takeNoNumber of rules to return (default 50, max 100)
categoryNoFilter by category: person, location, internet, date_time, finance, identifier, media or misc
isBuiltInNotrue for built-in rules only, false for custom rules only. Omit for both.
mockServerIdYesThe public Id (Guid) of the mock server

Schema Changelog

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

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

The readOnlyHint annotation already signals no side effects, and the description's use of 'List' reinforces the read-only behavior. It also discloses the default filtering behavior for built-in rules. No contradictions exist between description and 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 concise, using two sentences to convey purpose, scope, filtering defaults, and context requirements. There is no unnecessary detail or redundancy.

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?

The description provides enough context for the tool's purpose and default behavior, and all parameters are documented in the schema. Since there is no output schema, the lack of explicit return format is acceptable, though a brief note on result shape would make it fully complete.

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 schema already provides 100% coverage with descriptions for all parameters, so the description adds little beyond what is in the schema. The 'Requires project context' note adds a small hint, but the parameters are adequately documented in the schema itself.

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 the tool lists Smart Mock matching rules for one mock server, and differentiates itself from generic mock rule listing by specifying the scope ('of one mock server'). It also clarifies the default inclusion of built-in rules, setting it apart from related list tools.

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 practical usage guidance by explaining that built-in rules are included unless filtered, and notes that project context is required. It does not explicitly compare to sibling tools, but the resource and scope are clear enough for an agent to choose this tool appropriately.

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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TDQS

A3.9/5.0
Disambiguation4/5

The tools are mostly distinct with clear descriptions. Some pairs like get_header_policies vs get_resolved_headers or get_environment_verification vs get_monitoring_sync_status could be slightly confusing, but the descriptions clarify scope and purpose.

Naming Consistency5/5

All tools follow a consistent snake_case verb_noun pattern (get_, list_, create_, update_, manage_, etc.). Even the few bare verbs like 'search' and 'set_context' are consistent with the naming scheme.

Tool Count1/5

With 165 tools, the server is extremely heavy. This far exceeds the 'too many' threshold of 25+, making it difficult for an agent to navigate and select the right tool efficiently.

Completeness5/5

The tool surface covers a very broad API lifecycle domain: specs, environments, test cases, monitors, mock servers, security, governance, documentation, and team management. Read and write operations are present across most areas, with no obvious missing core functionality.

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