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ultralytics-mcp

by amanharshx
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TypeScript
Remote

dataset_images_list

Read-only

List images from a dataset using a slug or URI, with filters for split, class, label state, search, and pagination to locate specific images.

Instructions

List images in a dataset by slug, owner/slug, or a ul://owner/datasets/slug URI with optional filtering.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum images to return.
splitNoDataset split to filter by, for example train, val, or test.
offsetNoImages to skip.
searchNoImage name or metadata search.
datasetYesDataset ref by slug, owner/slug, or a ul://owner/datasets/slug URI.
classIdsNoClass IDs to filter by. An empty array is treated as no filter (all images match), not as a filter that excludes everything.
hasLabelNoFilter by annotation state.
includeImageUrlsNoInclude signed full-size image URLs.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed8 schema fields changedv0.1.13
    • addedInput schema / properties / classIds / description
      Added value: +"Class IDs to filter by. An empty array is treated as no filter (all images match), not as a filter that excludes everything."
    • 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."
    • addedInput schema / properties / hasLabel / description
      Added value: +"Filter by annotation state."
    • addedInput schema / properties / includeImageUrls / description
      Added value: +"Include signed full-size image URLs."
    • addedInput schema / properties / limit / description
      Added value: +"Maximum images to return."
    • addedInput schema / properties / offset / description
      Added value: +"Images to skip."
    • addedInput schema / properties / search / description
      Added value: +"Image name or metadata search."
    • addedInput schema / properties / split / description
      Added value: +"Dataset split to filter by, for example train, val, or test."
  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. Addedv0.1.6

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds little behavioral detail beyond 'optional filtering' and accepted dataset references; it does not mention pagination defaults, result shape, or signed URL behavior.

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?

A single, front-loaded sentence contains the core verb, resource, accepted reference forms, and the existence of filters. Every word contributes 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 straightforward read-only list operation with 100% schema coverage and safety annotations, the description is largely sufficient. Minor gaps exist around return format and default pagination, but these are not critical 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?

Schema description coverage is 100%, so the baseline applies. The description mostly repeats the dataset reference formats already present in the schema and provides no additional meaning for the filter parameters beyond the generic phrase 'optional filtering.'

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 uses a specific verb ('List'), names the resource ('images in a dataset'), and enumerates the accepted identifier formats (slug, owner/slug, URI). It is clearly distinct from sibling tools like datasets_list, which lists datasets rather than images.

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 when to use the tool by naming its action and resource, but it does not explicitly state when to choose it over alternatives or mention any exclusions. The usage context is inferable but not directly articulated.

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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