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@argosvix/mcp-server

@argosvix/mcp-server

by argosvix
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

get_eval_dataset

Fetch a specific evaluation dataset's details and all its items using the dataset ID.

Instructions

Fetch one dataset's detail plus all of its items (GET /v1/eval-datasets/:id). datasetId is list_eval_datasets.datasets[].id.

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": {
      "datasetId": "<datasetId>"
    },
    "name": "get_eval_dataset"
  }
}

Input Schema

NameRequiredDescriptionDefault
datasetIdYesTarget dataset id (list_eval_datasets.datasets[].id)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.30.0-alpha.14

TDQS

A4.2/5.0
Behavior4/5

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

Describes return content (detail plus all items) and idempotent fetch behavior. No annotations provided, so description carries full burden. Could mention that it is read-only.

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?

Single sentence, front-loaded with verb, no extraneous words. Efficient and clear.

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

Completeness4/5

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

Adequately describes purpose, endpoint, and parameter source for a simple fetch tool. Lacks details on response format, but no output schema exists. Could mention potential limitations like pagination.

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?

Schema covers parameter with name, type, and basic description. Description adds value by specifying the source (list_eval_datasets.datasets[].id), aiding correct invocation.

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?

Description clearly states the action (Fetch), resource (one dataset's detail plus all items), and explicit endpoint (GET /v1/eval-datasets/:id). It distinguishes from siblings like list_eval_datasets and delete_eval_dataset.

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?

No explicit when-to-use or when-not-to-use guidance. Implicitly indicates dataset ID comes from list_eval_datasets, but does not compare with siblings like get_eval_run or get_eval_criterion.

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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