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multi-model-companion

multi-model-companion

by Reederey87
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

health_check

Verify connectivity to CLIProxyAPI and availability of configured companion models, without running inference.

Instructions

Verify connectivity to CLIProxyAPI and availability of configured companion models. This performs no model inference.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "health_check"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

No annotations are provided, so the description carries the behavioral disclosure burden. It explicitly states that the tool performs no model inference, signaling a lightweight, read-only operation. It does not detail output structure or potential error behaviors, but these are less critical given the tool has no parameters.

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 two concise sentences. The first sentence states the primary purpose, and the second adds a meaningful constraint ('no model inference') without unnecessary filler.

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

Completeness5/5

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

Given zero parameters and the presence of an output schema, the description is sufficient to understand the tool's scope and behavior. It correctly sets expectations for connectivity and availability checks without promising inference or model interactions.

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 the baseline is 4 per the rubric. The description provides no parameter information because none is needed; there is nothing to clarify beyond the empty schema.

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 ('Verify') and names the exact resources (CLIProxyAPI connectivity and companion model availability). It clearly distinguishes its purpose from siblings like list_companion_models, which would list models rather than check their health.

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

Usage Guidelines4/5

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

The description implies when to use the tool: when you need to verify connectivity to CLIProxyAPI and availability of companion models. It does not explicitly exclude alternatives or state 'when not to use', but the unique purpose is clear enough to guide selection.

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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