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@argosvix/mcp-server

@argosvix/mcp-server

by argosvix
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

delete_eval_dataset

Delete a golden dataset with cascade removal of items while preserving historical eval runs and scores. Provide the dataset ID.

Instructions

Delete a golden dataset (DELETE /v1/eval-datasets/:id, Pro+ only). Items are cascade-deleted. Past eval runs / scores remain.

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": "delete_eval_dataset"
  }
}

Input Schema

NameRequiredDescriptionDefault
datasetIdYesId of the dataset to delete

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.30.0-alpha.14

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description effectively discloses key behaviors: cascade deletion of items and preservation of past eval runs/scores. It could additionally note irreversibility but is otherwise transparent.

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?

Two concise sentences that front-load the core purpose, endpoint, and tier. Every sentence adds value with no redundancy.

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?

For a simple delete tool with one parameter and no output schema, the description covers the essential behavioral context (cascade, data retention). It could mention irreversibility but remains adequately complete.

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?

The input schema already fully covers the single parameter (datasetId) with a description. The tool description adds no additional meaning beyond what the schema provides, so baseline score applies.

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 clearly states the action ('delete a golden dataset'), specifies the HTTP method and endpoint, and mentions the Pro+ tier restriction. It distinguishes from sibling tools like create_eval_dataset and list_eval_datasets.

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?

The description implies usage when wanting to delete a dataset but does not explicitly state when to use this tool instead of alternatives, nor does it provide exclusions or prerequisites beyond the tier.

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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