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ai-nglish

Ainglish MCP Server

Official
by ai-nglish

get_adoption_trends

Retrieve adoption trends for Ainglish constructs: view recent usage history and receive explicit alerts for missing or expiring coverage, so you can assess language adoption without misreading absent data as zero.

Instructions

Append-only adoption history, descriptive recent-usage trends, and explicit missing or expiring coverage alerts. Missing coverage is never represented as observed zero.

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

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the burden. It discloses key behaviors: 'Append-only' indicates historical immutability, and 'Missing coverage is never represented as observed zero' is a critical caveat about data representation. It also lists the three output components. This is substantial behavioral context beyond what the empty schema provides.

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 tight two-sentence composition that front-loads the primary purpose ('append-only adoption history') and then layers supporting details (trends, alerts) with a critical caveat. No filler 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?

For a zero-parameter tool with no output schema, the description provides a reasonable mental model: it names the three content areas and a key data-interpretation rule. However, details like the exact time range for 'recent' or the output format are left unspecified, which could be relevant for an agent deciding whether the returned data suits a query.

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?

There are zero parameters, so the schema imposes no burden. Per the rubric, a zero-parameter tool receives a baseline of 4. The description adds no parameter-specific meaning because none are needed.

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 resource ('adoption trends') and the kind of data provided: 'append-only adoption history, descriptive recent-usage trends, and explicit missing or expiring coverage alerts.' It goes beyond a tautology and implicitly distinguishes from siblings like get_adoption_snapshot by mentioning trends and alerts, but it does not explicitly name alternatives.

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 usage for adoption trends and alerts, but it does not provide explicit when-to-use or when-not-to-use guidance, nor does it reference any sibling tools (e.g., get_adoption_snapshot). The absence of comparison leaves an agent to infer the appropriate 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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