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urai-router

urai-router

Official
by etside
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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urai_explain

Explains how a model or alias is routed, which providers qualify, and how many API keys are ready for failover.

Instructions

Explain how a model or alias would be routed, which providers qualify and how many keys are ready.

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": "urai_explain"
  }
}

Input Schema

NameRequiredDescriptionDefault
modelNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It implies a non-mutating explanation and discloses the shape of the answer (routing path, eligible providers, key counts), but says nothing about what happens with an unknown or omitted model, whether multiple candidate routes are returned, or whether it triggers any provider calls.

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

Conciseness4/5

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

One compact sentence that front-loads the core action and then enumerates the outputs. No filler; the only shortfall is that nothing about the input or fallback behavior is included in the little space used.

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?

For a simple read-oriented diagnostic with one optional parameter and no output schema, the description covers what the result will contain, which is the main need. It leaves the optional-parameter behavior and error cases unaddressed, so an agent still has to guess at edge cases.

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?

Schema coverage is 0% and the single 'model' parameter is undocumented in the schema. The description partially compensates by noting it accepts a model or an alias, which is real added meaning, but it does not say the parameter is optional or what happens when it is omitted.

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?

Names a specific verb (explain) and a specific resource (routing of a model/alias), plus the outputs of interest: qualifying providers and ready key counts. That distinguishes it from data-mutating siblings like urai_refresh or urai_setup, though it never explicitly contrasts with urai_check or urai_models.

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?

Usage is only implied: an agent can infer this is the diagnostic/what-if tool for routing questions, but the description never says when to pick it over urai_check, urai_models or urai_health, nor does it state prerequisites such as needing configuration to already exist.

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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