dare-mcp-server

Cancel a Dare generation

dare_cancel_generation

Idempotent

Cancel an ongoing AI generation to prevent wasted credits when a job was started by mistake. Stop the process immediately and avoid unnecessary charges.

Instructions

Cancel an in-flight generation. Use when a job was started by mistake, to stop it consuming credits.

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": {
      "generation_id": "<generation_id>"
    },
    "name": "dare_cancel_generation"
  }
}

Input Schema

Name	Required	Description	Default
`generation_id`	Yes	Generation id to cancel.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 5, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already indicate this is a mutating, non-destructive, idempotent operation. The description adds useful behavioral context beyond those hints: it only applies to in-flight generations and its purpose is to stop credit consumption. No contradiction with annotations is present.

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 short sentences deliver the core action immediately and then provide the key use case. There is no redundant or filler content, and the most critical information is front-loaded.

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?

This is a simple one-parameter tool with no output schema and complete schema documentation. The description, combined with the annotations, gives an agent everything needed to invoke it correctly and understand its effect.

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 has 100% coverage for the single parameter generation_id, with a clear description. The tool description does not add extra meaning beyond the schema, but the schema itself is sufficient, so a baseline score of 3 is appropriate.

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 ('Cancel'), a specific resource ('an in-flight generation'), and clarifies the scope ('in-flight') so it is distinct from deleting a completed or stored generation. This clearly differentiates it from sibling tools like dare_delete_generation.

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?

The description explicitly says when to use it: when a job was started by mistake and to stop credit consumption. It does not explicitly state when not to use it or mention alternatives like delete_generation, but the 'in-flight' qualifier provides a clear context boundary.

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

Deploy Server