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Terraform Engine MCP Server

Terraform Engine MCP Server

by asadongit
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

get_task_schema

Retrieve the metadata and input schema for a registered task, showing required parameters and structure for executing the task.

Instructions

Get the metadata and input schema (JSON Schema) for a registered task.
Args:
    task_name: The unique alphanumeric name of the task.

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": {
      "task_name": "<task_name>"
    },
    "name": "get_task_schema"
  }
}

Input Schema

NameRequiredDescriptionDefault
task_nameYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries full burden. It correctly indicates a read operation ('Get'), but does not disclose potential errors (e.g., task not found) or any side effects. Adequate but lacks depth.

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 extremely concise: two sentences with no wasted words. The first sentence is a clear one-liner defining the purpose, and the second describes the single parameter. Front-loaded and efficient.

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

Completeness4/5

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

Given the tool's simplicity (one parameter, output schema available), the description is mostly complete. It covers the basic behavior, but could mention that the task must exist or the tool will return an error. Still adequate overall.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate. It adds 'The unique alphanumeric name of the task.' which clarifies the expected format and uniqueness of the task_name parameter, providing meaningful context beyond the schema.

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 'Get the metadata and input schema (JSON Schema) for a registered task.' It uses a specific verb and resource, and naturally distinguishes from sibling tools like list_tasks (which lists tasks) and provision_task (which creates tasks).

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?

The description implies usage for retrieving schema but provides no explicit guidance on when to use this tool versus alternatives (e.g., before provisioning). No exclusions or prerequisites are mentioned.

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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