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llm_judge_get

Read-only

Get one LLM-as-a-judge evaluation template.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "templateId": "<templateId>"
    },
    "name": "llm_judge_get"
  }
}

Input Schema

NameRequiredDescriptionDefault
templateIdYesEvaluation template UUID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered without the description. The description adds no behavioral context beyond that — no note on error behavior for an unknown UUID, caching, or visibility of templates across scopes — so it earns only baseline credit.

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?

A single short sentence with the resource front-loaded and zero filler. It is appropriately sized for a trivial lookup, though it is so terse that it leaves no room for any differentiating detail.

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 one-parameter read tool with full annotation and schema coverage, the description is minimally sufficient to invoke it correctly. However, with no output schema, the agent has no idea what a returned template contains (prompt, model, scoring criteria, version), which is a real gap for deciding whether to call this versus llm_judge_list.

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?

With a single parameter at 100% schema description coverage ('Evaluation template UUID', format=uuid), the schema carries full burden and the description need not elaborate. The description adds nothing beyond it, but nothing is required.

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?

The description gives a specific verb ('Get') and a specific resource ('one LLM-as-a-judge evaluation template'), and the singular 'one' implicitly distinguishes it from the sibling llm_judge_list. It stops short of naming the sibling tools, but the purpose is unambiguous.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no statement that templateId should come from llm_judge_list or llm_judge_create, and no mention of what happens when the ID does not exist. The only usage signal is the implicit 'fetch by identifier' reading of 'Get one'.

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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