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MCP Vibe Coding Tools

MCP Vibe Coding Tools

by ammilam
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

gcloud_run_services_describe

Retrieve detailed configuration and status of a Cloud Run service by providing its name and region. Get metadata, revision details, and deployment settings to understand service behavior.

Instructions

Get detailed information about a Cloud Run service

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": {
      "service_name": "<service_name>",
      "region": "<region>"
    },
    "name": "gcloud_run_services_describe"
  }
}

Input Schema

NameRequiredDescriptionDefault
regionYesRegion where the service is deployed
platformNoCloud Run platformmanaged
service_nameYesName of the Cloud Run service

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only says 'Get detailed information' without specifying what information is returned, whether the operation is read-only, what permissions are required, or any side effects. This is insufficient for a tool that potentially returns complex data.

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, clear sentence that directly states the tool's purpose. There is no fluff or redundant information, making it maximally concise for its content.

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?

Given the tool has 3 parameters, no output schema, and no annotations, the description is too brief. It does not explain what detailed information is returned, any constraints (e.g., service must exist), or how to interpret the output. This leaves significant gaps for an AI agent to correctly invoke and use the tool.

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 input schema already documents each parameter. The description adds no extra meaning beyond what the schema provides. A baseline score of 3 is appropriate since the schema does the heavy lifting, but the description could add context on parameter usage (e.g., format of region, impact of platform enum).

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 clearly states the tool retrieves detailed information about a Cloud Run service, using the verb 'Get' and specifying the resource. However, it does not differentiate from the sibling tool 'gcloud_run_services_list', which lists services, but the purpose is still unambiguous.

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. There is no mention of prerequisites, when not to use it, or which sibling tools might be better suited for different scenarios.

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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