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cancel_model_request

DestructiveIdempotent

Cancel a queued Model API request before it starts processing. Get immediate confirmation or know if it's too late to cancel.

Instructions

Cancel a queued Model API request.

Backs ``POST /v1/requests/{request_id}/cancel``. Returns
``cancelled`` if accepted, ``not_cancellable`` if the request is
already in progress or finished.

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": {
      "request_id": "<request_id>"
    },
    "name": "cancel_model_request"
  }
}

Input Schema

Name	Required	Description	Default
`request_id`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.1.0Sep 7, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already mark the destructive and idempotent behavior; the description adds the exact return tokens ('cancelled' vs 'not_cancellable') and the state boundary (queued vs in-progress/finished), going beyond the structured fields. No contradiction with annotations.

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 sentences, action and endpoint first, return behavior second. Every sentence contributes; no filler or redundant restatement of the schema.

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 one-parameter cancellation tool with no output schema, this is complete: it names the operation, the endpoint, the accepted state, and the exact response tokens. An agent has enough to select, invoke, and interpret the result.

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?

With 0% schema description coverage the description must carry parameter meaning. The endpoint path indicates request_id is the identifier of the queued Model API request to cancel, but the description gives no format, source, or further constraints, so it only partially compensates.

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 names a specific verb ('Cancel'), resource ('queued Model API request'), and the backing endpoint, and the 'queued' qualifier distinguishes it from cancel_request and cancel_training_job by scope. It also states the possible outcomes, making the tool's purpose unambiguous.

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?

It clearly says this applies to queued Model API requests and that in-progress or finished requests are not cancellable, which tells an agent when the call will succeed. It does not explicitly name sibling alternatives, so it stops short of 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.