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Glama

Get Fixture Usage

get_fixture_usage
Read-only

Inspect a project fixture. view 'used_by' (default) lists everything referencing it — mock rules, test cases, seeds, doc examples — which is what to check before changing or deleting it; view 'versions' lists its saved versions with their content. Requires project context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
viewNoWhat to read: 'used_by' (default) or 'versions'used_by
fixtureIdYesPublic Id (Guid) of the fixture

Schema Changelog

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

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

The description states it is an inspect/read operation, aligning with the readOnlyHint annotation. It discloses what each view returns (references or versions with content), adding context beyond the annotation's simple read-only flag. No destructive behavior is implied, consistent with the lack of a destructiveHint.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences and largely to the point. It packs a lot of detail into a semicolon-separated list, which slightly reduces readability, but remains efficient and well-structured.

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?

With no output schema, the description explains the return content for each view, which is sufficient for a simple two-parameter tool. It lacks explicit mention of error cases or pagination, but these are not critical for basic usage and the description covers essential behavior.

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?

The schema already covers both parameters with descriptions and a default. The tool description adds meaning by explaining what the 'used_by' view lists (mock rules, test cases, seeds, doc examples) and what 'versions' returns (saved versions with content), going beyond the schema's terse descriptions.

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 uses a specific verb ('Inspect') and identifies the resource ('project fixture') with two distinct views ('used_by' and 'versions'), clearly differentiating it from sibling tools like get_fixture (which likely returns fixture details) and list_fixtures.

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?

It provides clear when-to-use guidance: 'used_by' is for checking before changing or deleting a fixture, and 'versions' is for viewing saved versions. Also notes the prerequisite 'Requires project context.' However, it does not explicitly name alternative tools to compare against.

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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