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Glama
ai-nglish

Ainglish MCP Server

Official
by ai-nglish

get_protocols

Retrieve the public measurement protocols that define the metric criteria for evaluating AI language constructs, enabling transparent and consistent assessment.

Instructions

The measurement protocols — the public metric definitions a construct is judged against.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes what protocols are semantically, but does not state that the tool returns a list of protocols, whether any pagination or filtering applies, or whether any special access is needed. The word 'public' hints at a read-friendly operation, but the description does not explicitly define the 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 sentence that does not waste words. It gives the essential semantic content without repetition or unnecessary qualifiers.

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 zero-parameter getter with no annotations and no output schema, the description is nearly complete: it names the resource, clarifies its meaning, and implies the return value. It could be more explicit about the response format or whether all protocols are returned, but the low complexity of the tool makes this a minor gap.

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 tool has zero parameters and an empty input schema, so there are no parameter semantics for the description to clarify. The description need not compensate for any paramter gaps. The '0 parameters = baseline 4' rule applies.

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 identifies the resource as 'measurement protocols' and explains that they are 'public metric definitions a construct is judged against.' It stops short of using an explicit verb like 'retrieves' or 'lists,' but the meaning is clear and the resource is well distinguished from many sibling tools.

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 when this tool is relevant — when an agent needs measurement protocols or public metric definitions — but it never states usage explicitly or contrasts it with alternatives. There are no exclusions or when-not-to-use guidance, so the agent must infer the intended 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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