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H3 Cloud MCP

H3 Cloud MCP

by lst016
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

h3_cancel_job

Cancels a queued H3 audio-video generation job or requests interruption of the specified running job by job ID.

Instructions

Remove a queued H3 job or request interruption of that exact running job.

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": {
      "job_id": "<job_id>"
    },
    "name": "h3_cancel_job"
  }
}

Input Schema

NameRequiredDescriptionDefault
job_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses that queued jobs are removed while running jobs are only interrupted on request, but it omits permissions, idempotency, error behavior, and whether interruption is immediate or cooperative.

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 a single front-loaded sentence with no wasted words. The queued-versus-running distinction is expressed compactly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a destructive cancellation tool with no annotations and no output schema, the description is too thin. It covers the core queued/remove vs. running/interrupt behavior but leaves out return values, error cases, permissions, and post-cancellation effects.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single job_id parameter has 0% schema description coverage, so the description should explain its format or provenance. It only implies the ID identifies the exact job and adds no details about where to obtain it or whether completed jobs are valid.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action and resource: remove a queued H3 job or interrupt a running one. It also distinguishes queued versus running handling, but it does not explicitly differentiate itself from sibling tools such as h3_job_status or h3_generate.

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?

Use is implied by the verb 'cancel' and the queued/running distinction, so an agent can infer it should be called to stop a job. However, there is no explicit guidance on when not to use it, prerequisites, or alternatives such as checking status first.

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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