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list_scaling_activities

Retrieve recent scaling activities for an Auto Scaling Group to monitor capacity changes and troubleshoot scaling events in AWS.

Instructions

Describes recent scaling activities for an Auto Scaling Group.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
auto_scaling_group_nameYesThe name of the Auto Scaling Group.

Implementation Reference

  • Handler function that implements the 'list_scaling_activities' tool. It takes an Auto Scaling Group name, calls DescribeScalingActivitiesCommand via asgClient, maps the response to a simplified activity list, and returns it as JSON.
    if (name === "list_scaling_activities") {
        const groupName = (args as any).auto_scaling_group_name;
        const command = new DescribeScalingActivitiesCommand({ AutoScalingGroupName: groupName, MaxRecords: 10 });
        const response = await asgClient.send(command);
    
        const activities = response.Activities?.map(a => ({
            ActivityId: a.ActivityId,
            Description: a.Description,
            Cause: a.Cause,
            StartTime: a.StartTime,
            StatusCode: a.StatusCode
        })) || [];
    
        return { content: [{ type: "text", text: JSON.stringify(activities, null, 2) }] };
    }
  • src/index.ts:741-751 (registration)
    Registration of the 'list_scaling_activities' tool in the ListToolsRequestSchema handler, including the tool name, description, and input schema definition.
    {
        name: "list_scaling_activities",
        description: "Describes recent scaling activities for an Auto Scaling Group.",
        inputSchema: {
            type: "object",
            properties: {
                auto_scaling_group_name: { "type": "string", "description": "The name of the Auto Scaling Group." }
            },
            required: ["auto_scaling_group_name"]
        }
    },
  • Input schema for the 'list_scaling_activities' tool, requiring 'auto_scaling_group_name' as a string.
    inputSchema: {
        type: "object",
        properties: {
            auto_scaling_group_name: { "type": "string", "description": "The name of the Auto Scaling Group." }
        },
        required: ["auto_scaling_group_name"]
  • Import of AutoScalingClient and DescribeScalingActivitiesCommand used by the tool.
    import { AutoScalingClient, DescribeAutoScalingGroupsCommand, DescribeScalingActivitiesCommand } from "@aws-sdk/client-auto-scaling";
  • Initialization of the AutoScalingClient (asgClient) instance used to call AWS APIs for scaling activities.
    const asgClient = new AutoScalingClient({});
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'recent scaling activities' but doesn't specify time ranges, pagination, rate limits, authentication needs, or what constitutes 'recent.' This leaves significant gaps in understanding the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose without unnecessary details. However, it could be slightly more structured by explicitly mentioning the parameter or output expectations to improve clarity.

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 no annotations and no output schema, the description is incomplete for a tool that likely returns complex data (e.g., lists of activities). It doesn't cover return formats, error handling, or behavioral nuances, leaving the agent with insufficient context to use it effectively.

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?

The input schema has 100% description coverage, clearly documenting the single required parameter. The description adds no additional meaning beyond the schema, such as format examples or constraints, so it meets the baseline for high schema coverage without compensating value.

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's purpose with a specific verb ('Describes') and resource ('recent scaling activities for an Auto Scaling Group'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_auto_scaling_groups' or other monitoring tools, which would require a 5.

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?

The description provides no guidance on when to use this tool versus alternatives, such as how it differs from general monitoring tools or when 'recent' scaling activities are relevant. It lacks context on prerequisites or exclusions, leaving usage unclear.

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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