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RadiumGu
by RadiumGu

get_experiment_template

Retrieve detailed configuration and parameters for AWS Fault Injection Service experiment templates to analyze chaos engineering setups.

Instructions

Get detailed information about a specific AWS FIS experiment template.

Args:
    template_id: ID of the experiment template to retrieve
    region: AWS region to query (default: us-east-1)
    
Returns:
    JSON string containing detailed template information

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
template_idYes
regionNous-east-1

Implementation Reference

  • The handler function that executes the tool logic: retrieves AWS FIS experiment template by ID using boto3, formats key fields into a JSON response.
    def get_experiment_template(template_id: str, region: str = "us-east-1") -> str:
        """
        Get detailed information about a specific AWS FIS experiment template.
        
        Args:
            template_id: ID of the experiment template to retrieve
            region: AWS region to query (default: us-east-1)
            
        Returns:
            JSON string containing detailed template information
        """
        try:
            fis = boto3.client('fis', region_name=region)
            response = fis.get_experiment_template(id=template_id)
            
            # Format the response for better readability
            template = response.get('experimentTemplate', {})
            formatted_template = {
                'id': template.get('id'),
                'description': template.get('description'),
                'targets': template.get('targets', {}),
                'actions': template.get('actions', {}),
                'stopConditions': template.get('stopConditions', []),
                'roleArn': template.get('roleArn'),
                'tags': template.get('tags', {})
            }
            
            return json.dumps(formatted_template, indent=2)
        except Exception as e:
            return f"Error retrieving experiment template: {str(e)}"
  • Registers the get_experiment_template tool with the FastMCP server using app.tool() decorator.
    app.tool()(get_experiment_template)
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states it retrieves detailed information but doesn't disclose behavioral traits like authentication needs (AWS credentials), rate limits, error handling, or whether it's a read-only operation. The description adds minimal context beyond the basic action, leaving significant gaps for a tool interacting with AWS services.

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 clear sections for Args and Returns. Every sentence earns its place: the first states the action, the Args explain parameters concisely, and the Returns sets expectations. No wasted words or redundancy.

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

Completeness3/5

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

Given no annotations and no output schema, the description is moderately complete. It covers the basic purpose and parameters adequately but lacks context on authentication, error handling, or detailed return structure (only stating 'JSON string'). For a tool with AWS integration and 2 parameters, it should provide more operational guidance to be fully helpful.

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 meaningful semantics for both parameters: template_id is described as 'ID of the experiment template to retrieve', and region as 'AWS region to query (default: us-east-1)'. This clarifies purpose and default values beyond the schema's basic types, though it doesn't detail format constraints (e.g., region naming conventions).

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 verb 'Get' and the resource 'detailed information about a specific AWS FIS experiment template', making the purpose explicit. It distinguishes from siblings like list_experiment_templates (which lists multiple) and create_experiment_template (which creates new ones). However, it doesn't explicitly contrast with get_experiment (which retrieves experiment instances rather than templates), leaving slight room for improvement.

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 when you need detailed info for a specific template ID, but doesn't explicitly state when to use this vs. alternatives like list_experiment_templates (for browsing) or get_experiment (for experiment instances). No exclusions or prerequisites are mentioned, such as authentication requirements or region availability.

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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