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MCP Vibe Coding Tools

MCP Vibe Coding Tools

by ammilam
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TypeScript
Local

gcloud_dataflow_jobs_cancel

Cancel a running Dataflow job by providing its job ID and region. Stop active pipeline execution to manage costs or correct errors.

Instructions

Cancel a running Dataflow 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": "gcloud_dataflow_jobs_cancel"
  }
}

Input Schema

NameRequiredDescriptionDefault
job_idYesDataflow job ID to cancel
regionNoRegion where the job is runningus-central1

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior1/5

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

The description lacks any behavioral disclosure beyond the verb 'Cancel'. It does not indicate whether the operation is irreversible, what permissions are needed, or what happens to the job (e.g., graceful vs forceful stop). With no annotations, this is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single, front-loaded sentence with no wasted words. However, it is perhaps too terse for a mutation tool that could benefit from a bit more context.

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?

The tool has no output schema and the description does not explain what happens after cancellation, success/failure signals, or the impact on the job. It is not sufficiently complete for an agent to use confidently.

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 already describes both parameters with 100% coverage (job_id and region). The description adds no additional meaning, so it meets the baseline but does not exceed it.

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 clearly states the verb 'Cancel' and the resource 'a running Dataflow job', which is specific and distinguishes it from sibling tools like list and describe.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives, nor any prerequisites (e.g., job must be running, permission requirements). The description only states the basic action.

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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