SubcueAI

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.

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.

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.

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.

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.

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.

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

With no annotations provided, the description carries the burden of behavioral disclosure. The verb 'Get' implies a read-only operation, and 'live' suggests dynamic data rather than cached values, but the description does not explicitly state that the operation has no side effects or require authentication. It provides moderate behavioral transparency but not full disclosure.

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

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

The description is a single, tightly written sentence that front-loads the primary purpose and uses no filler words. Every element — subscription plans, pricing, live credit rates, per-action and per-minute — adds value and justifies its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

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 covers the main information categories returned (plans, pricing, credit rates) and even adds the per-action/per-minute granularity. However, it does not specify the response shape, currency, or whether plans share the same rates, leaving minor gaps in context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the schema fully covers parameter semantics and the description adds no param details. Per the baseline for 0-param tools, a score of 4 is appropriate since there is nothing meaningful to add.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Get') and identifies the exact resource: SubcueAI subscription plans, pricing, and live credit rates per action and per minute. It clearly differentiates itself from the sibling tool get_latest_version by focusing on pricing rather than version information.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool should be used when pricing, plans, or credit rates are needed, but it does not explicitly state when to use it versus get_latest_version or provide any exclusions. The usage context is inferable from the resource description but not directly articulated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.