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WYRE-AI

Yeastar MCP Server

by WYRE-AI

yeastar_get_system_capacity

Check current extension, trunk, and concurrent-call usage against licensed capacity limits to identify overages and plan upgrades.

Instructions

Get current extension/trunk/concurrent-call usage against this appliance's licensed capacity limits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
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 disclosing behavioral traits. It implies a read-only operation ('Get') but does not explicitly state that it is non-mutating or whether it requires any permissions. It also fails to describe the return format or any potential side effects. This is a significant gap for a tool with zero annotation coverage.

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, concise sentence that front-loads the main action ('Get current ... usage') and includes the key context (against licensed capacity limits). There is no unnecessary verbiage, making it highly efficient for an agent to parse.

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

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simplicity of the tool (no parameters, no output schema, no annotations), the description gives a basic understanding of what it does but does not explain the return structure or edge cases (e.g., what happens when capacity is exceeded). Since there is no output schema, the description should clarify what the agent can expect in terms of data format, but it falls short. This is adequate but not complete.

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, so there is nothing to document. According to the rubric, a 0-parameter tool gets a baseline of 4. The description does not add parameter semantics because none exist, and the schema coverage is 100% (empty object), so this score is appropriate.

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: current extension/trunk/concurrent-call usage against licensed capacity limits. It distinguishes itself from siblings like yeastar_get_system_information by specifying the exact metrics being retrieved, leaving no ambiguity about what the tool does.

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?

There is no explicit guidance about when to use this tool versus alternatives, and no mention of exclusions or alternatives. However, the purpose is evident from the name and description, so usage is implied rather than stated. A mention of when to prefer this over get_system_information would have improved the score.

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