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terraform-cloud-mcp

get_assessment_json_schema

Retrieve the JSON schema from Terraform Cloud assessment results to understand available resources and configuration options used during infrastructure evaluation.

Instructions

Retrieve the JSON schema file from an assessment result.

Gets the JSON schema representation of the provider schema used during the assessment, providing information about available resources and their configuration options.

API endpoint: GET /api/v2/assessment-results/{assessment_result_id}/json-schema

Args: assessment_result_id: The ID of the assessment result to retrieve schema for (format: "asmtres-xxxxxxxx")

Returns: The JSON schema file containing provider information. The redirect is automatically followed.

Note: This endpoint requires admin level access to the workspace and cannot be accessed with organization tokens.

See: docs/tools/assessment_results.md for reference documentation

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
assessment_result_idYes

Implementation Reference

  • The main async handler function for the 'get_assessment_json_schema' tool. It validates the assessment_result_id using AssessmentOutputRequest and performs an API GET request to /assessment-results/{id}/json-schema, returning the JSON schema with accept_text=True to handle large files.
    @handle_api_errors
    async def get_assessment_json_schema(assessment_result_id: str) -> APIResponse:
        """Retrieve the JSON schema file from an assessment result.
    
        Gets the JSON schema representation of the provider schema used during the assessment,
        providing information about available resources and their configuration options.
    
        API endpoint: GET /api/v2/assessment-results/{assessment_result_id}/json-schema
    
        Args:
            assessment_result_id: The ID of the assessment result to retrieve schema for (format: "asmtres-xxxxxxxx")
    
        Returns:
            The JSON schema file containing provider information. The redirect is automatically followed.
    
        Note:
            This endpoint requires admin level access to the workspace and cannot be accessed
            with organization tokens.
    
        See:
            docs/tools/assessment_results.md for reference documentation
        """
        # Validate parameters
        params = AssessmentOutputRequest(assessment_result_id=assessment_result_id)
    
        # Make API request with text acceptance since it may be a large JSON file
        return await api_request(
            f"assessment-results/{params.assessment_result_id}/json-schema",
            accept_text=True,
        )
  • Pydantic input schema models used for validation in the handler. AssessmentOutputRequest (lines 58-70) inherits from AssessmentResultRequest (lines 39-56), defining 'assessment_result_id' with regex pattern '^asmtres-[a-zA-Z0-9]{8,}$' for the tool input.
    class AssessmentResultRequest(APIRequest):
        """Request model for retrieving assessment result details.
    
        Used to validate the assessment result ID parameter for API requests.
    
        Reference: https://developer.hashicorp.com/terraform/cloud-docs/api-docs/assessment-results#show-assessment-result
    
        See:
            docs/models/assessment_result.md for reference
        """
    
        assessment_result_id: str = Field(
            ...,
            # No alias needed as field name matches API parameter
            description="The ID of the assessment result to retrieve",
            pattern=r"^asmtres-[a-zA-Z0-9]{8,}$",  # Standard assessment result ID pattern
        )
    
    
    class AssessmentOutputRequest(AssessmentResultRequest):
        """Request model for retrieving assessment result outputs.
    
        Extends the base AssessmentResultRequest for specialized outputs like
        JSON plan, schema, and log output.
    
        Reference: https://developer.hashicorp.com/terraform/cloud-docs/api-docs/assessment-results#retrieve-the-json-output-from-the-assessment-execution
    
        See:
            docs/models/assessment_result.md for reference
        """
    
        pass  # Uses the same validation as the parent class
  • Registration of the 'get_assessment_json_schema' tool in the FastMCP server using the mcp.tool() decorator.
    mcp.tool()(assessment_results.get_assessment_json_schema)
Behavior4/5

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

With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: it specifies admin-level access requirements, token restrictions, and that redirects are automatically followed. However, it doesn't mention rate limits, error conditions, or response format details beyond 'JSON schema file'.

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 well-structured and front-loaded with the core purpose, followed by API endpoint details, parameter explanation, return value, and important notes. Every sentence earns its place, with no redundant information or unnecessary elaboration.

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?

For a single-parameter read operation with no annotations and no output schema, the description provides comprehensive context about purpose, usage, authentication requirements, and parameter details. The only minor gap is lack of explicit information about the structure of the returned JSON schema file.

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?

With 0% schema description coverage and only one parameter, the description adds significant value by explaining the parameter's purpose ('The ID of the assessment result to retrieve schema for') and providing format details ('format: "asmtres-xxxxxxxx"'). This fully compensates for the schema's lack of descriptions.

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 specific action ('Retrieve the JSON schema file') and resource ('from an assessment result'), distinguishing it from sibling tools like 'get_assessment_json_output' or 'get_assessment_result_details'. It provides a precise verb+resource combination with explicit scope.

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

Usage Guidelines5/5

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

The description explicitly states when to use this tool ('Retrieve the JSON schema file from an assessment result') and includes a critical 'Note' section specifying when NOT to use it ('cannot be accessed with organization tokens'). It also references alternative documentation ('See: docs/tools/assessment_results.md') for further context.

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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