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Latest SubcueAI Version

get_latest_version

Get the latest SubcueAI desktop app version and download info.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
platformNoPlatform, e.g. macos-arm64 or windows-x64

Schema Changelog

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

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description carries the disclosure burden. It clearly indicates a read-only retrieval, but it does not describe the response shape, behavior when platform is omitted, or any network/error characteristics.

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?

A single sentence conveys the action, resource, and output type with no filler or redundancy. It is appropriately sized for the tool's simplicity.

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 simple getter with one optional parameter, the description plus schema is mostly sufficient. The main gap is that it does not clarify behavior when platform is omitted or describe the exact return structure, but the low complexity prevents this from being a critical omission.

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 input schema already describes the platform parameter with examples, and schema coverage is 100%, so the description adds little beyond context. Baseline 3 is appropriate because no extra parameter-level guidance is needed.

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 ('Get') and clearly identifies the resource ('latest SubcueAI desktop app version and download info'). The sibling get_pricing is clearly different because pricing vs. version/download info are distinct outputs.

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 intended use is implied by the name and description, but there is no explicit statement of when to choose this tool over get_pricing or when not to use it. No alternatives or exclusions are mentioned.

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
Disambiguation5/5

The two tools target clearly separate concerns: version/download information versus subscription pricing. There is no overlap or ambiguity between them.

Naming Consistency5/5

Both tool names follow a consistent get_<noun> pattern using snake_case and informative nouns. The naming convention is uniform and predictable.

Tool Count3/5

With only two tools, the server feels minimal, though each tool serves a distinct and relevant purpose. This is borderline-thin for a product-related server but not excessive.

Completeness3/5

The server covers version and pricing queries but leaves obvious gaps such as feature information, system requirements, changelog, or support/contact tools. Agents can handle basic product questions but little else.