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amanharshx

ultralytics-mcp

by amanharshx
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TypeScript
Remote

datasets_delete

Destructive

Delete a dataset by slug, owner/slug, or URI. Images and annotations move to trash for a limited time, while models trained on the dataset remain intact.

Instructions

Delete a dataset by slug, owner/slug, or a ul://owner/datasets/slug URI. Deleting a dataset moves its images and annotations to trash with it; models trained on it are not deleted. Trashed items remain restorable for a bounded window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
datasetYesDataset ref by slug, owner/slug, or a ul://owner/datasets/slug URI.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.1.13
    • changedInput schema / properties / dataset / description
      Previous value: -"Dataset ref by slug, owner/slug, or ul:// URI."New value: +"Dataset ref by slug, owner/slug, or a ul://owner/datasets/slug URI."
  2. Changed1 schema field changedv0.1.12
    • changedInput schema / properties / dataset / description
      Previous value: -"Dataset ref by id, slug, username/slug, or ul:// URI."New value: +"Dataset ref by slug, owner/slug, or ul:// URI."
  3. Changed1 schema field changedv0.1.6
    • addedInput schema / properties / dataset / description
      Added value: +"Dataset ref by id, slug, username/slug, or ul:// URI."
  4. Addedv0.1.1

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the destructiveHint=true annotation, the description discloses critical side effects: images and annotations go to trash, models trained on the dataset are not deleted, and trashed items are restorable for a bounded window. This adds valuable behavioral context that an agent needs to know before invoking a destructive operation.

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 sentences with zero filler. The first sentence front-loads the action and identifier formats; the second sentence concisely explains the consequences. Every sentence earns its place, and the structure is optimal for quick agent parsing.

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?

For a destructive tool with one well-documented parameter and no output schema, the description covers everything an agent needs: how to specify the dataset, what happens to associated data (trash, models), and the restoration window. Nothing critical is missing for correct invocation.

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 schema already provides full coverage (100%) of the single 'dataset' parameter with a description listing the same formats (slug, owner/slug, ul:// URI). The tool description repeats this information without adding new semantic meaning, so it does not compensate beyond the schema baseline.

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 states a specific verb ('Delete') and the resource ('a dataset') along with the exact identifier formats (slug, owner/slug, ul:// URI). This clearly distinguishes it from sibling tools like datasets_list, datasets_get, and datasets_create, which serve different purposes.

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 you want to delete a dataset. However, it does not explicitly state when to prefer this over alternatives (e.g., dataset_version_delete) or mention any conditions or exclusions. There is no explicit when/not guidance, but the context is clear enough for a straightforward delete operation.

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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