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Facets-cloud

Facets Module MCP Server

by Facets-cloud

validate_module

Validates a Terraform module directory against FTF standards, checking structure, formatting, required files, and output type references in the Facets control plane.

Instructions

Tool to validate a module directory using FTF CLI.

This tool checks if a Terraform module directory meets the FTF standards. It validates the structure, formatting, required files, and output types of the module. It also checks that all output types referenced in outputs and inputs blocks exist in the Facets control plane.

Args:

  • module_path (str): The path to the module.

  • check_only (bool): Flag to only check formatting without applying changes.

  • skip_terraform_validation_if_provider_not_found (bool): Flag to skip terraform validation during the process - send as true only if you see "Provider configuration not present" while validating.

Returns:

  • str: A JSON string with the output from the FTF command execution or error message if validation fails.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
module_pathYes
check_onlyNo
skip_terraform_validation_if_provider_not_foundNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses that the tool performs a read-only validation, checks multiple criteria, and returns a JSON string. This is sufficient for the agent to understand safety and outcome.

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 compact yet comprehensive, using a clear structure: a one-line summary, a paragraph explaining behavior, and bullet-pointed arguments and return. No wasted words.

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 has 3 parameters, no annotations, and an output schema, the description covers purpose, parameters, and return value adequately. It could be more complete by mentioning performance or error conditions, but it is sufficient for correct invocation.

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?

The input schema has 0% description coverage, but the description's docstring explains each parameter's purpose (module_path, check_only, skip_terraform_validation_if_provider_not_found). This adds significant meaning beyond the schema titles and defaults.

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 tool validates a module directory using FTF CLI, specifying what it checks (structure, formatting, required files, output types). This is specific and distinguishes it from sibling tools like discover_terraform_resources or fork_existing_module.

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 the tool is used when validation of module standards is needed, but it does not explicitly state when not to use it or mention alternatives. There is no clear guidance contrasting it with sibling tools.

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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