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ultralytics-mcp

by amanharshx
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TypeScript
Remote

auto_annotate_stop

Destructive

Stop or dismiss a dataset's auto-annotation run by slug or URI. Checks status first, then cancels an active run or clears a terminal one.

Instructions

Stop or dismiss a dataset's auto-annotation run by slug, owner/slug, or a ul://owner/datasets/slug URI. Reads status first and refuses without calling the endpoint when no run is active, since there is nothing to stop. When a run is active it sends the request and surfaces the server's own action verbatim rather than inferring it: cancelled for an active run stopped mid-flight, dismissed for a terminal run's summary being cleared, or none if nothing acted on. Ships ungated, consistent with training_cancel and export_cancel: an off-switch is never gated. An undismissed terminal run does not block the next start, so this never strands anything; dismissal moves no money.

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 changedv0.1.15
    • addedInput schema / additionalProperties
      Added value: +false
  2. 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."
  3. Addedv0.1.12

TDQS

A4.5/5.0
Behavior5/5

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

Goes well beyond annotations by disclosing the status-precheck/refusal behavior, the exact returned action verbs (cancelled/dismissed/none surfaced verbatim), the gating model ('ships ungated'), and two side-effect clarifications (undismissed terminal run doesn't block next start; dismissal moves no money). Annotations only flag destructive/readOnly, so this adds substantial context.

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?

Purpose and input forms are front-loaded in the first sentence, and each subsequent sentence adds a distinct behavioral fact (precheck, return verbs, gating, side effects). No filler or redundant restatement of the name.

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?

No output schema exists, yet the description explains the returned action vocabulary and the refusal path, plus side-effect and gating behavior. For a single-param mutation tool this leaves nothing an agent needs missing.

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 single 'dataset' parameter is already fully documented. The description repeats the same slug/owner-slug/URI forms without adding syntax or format detail beyond the schema, which is the expected baseline when the schema does the heavy lifting.

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?

States a specific verb (stop/dismiss) and resource (dataset's auto-annotation run), and enumerates the three accepted ref forms. An agent can distinguish it from auto_annotate_start and auto_annotate_status from the description alone.

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

Usage Guidelines4/5

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

Gives clear preconditions: it reads status first and refuses without calling the endpoint when no run is active, and it distinguishes mid-flight cancellation from clearing a terminal run's summary. It does not explicitly route the agent to a sibling (e.g. auto_annotate_status) for checking first, so it stops short of full when-to-use/when-not guidance.

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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