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by hackle-io

experiment-detail

Retrieve detailed information about a specific A/B test experiment by providing the experiment ID for accurate analysis and insights.

Instructions

Retrieves detailed information for a specific A/B test experiment.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
experimentIdYes

Implementation Reference

  • The handler function for the 'experiment-detail' tool. It takes an experimentId and fetches the detailed experiment information from the API using WebClient.get, then returns it as JSON text content.
    async ({ experimentId }) => {
      return {
        content: [
          {
            type: 'text',
            text: JSON.stringify(await WebClient.get(`/api/v1/experiments/${experimentId}`)),
          },
        ],
      };
    },
  • The input schema for the 'experiment-detail' tool, requiring a numeric experimentId.
    {
      experimentId: z.number(),
    },
  • src/index.ts:46-61 (registration)
    The registration of the 'experiment-detail' tool on the MCP server, including name, description, schema, and handler function.
      'experiment-detail',
      'Retrieves detailed information for a specific A/B test experiment.',
      {
        experimentId: z.number(),
      },
      async ({ experimentId }) => {
        return {
          content: [
            {
              type: 'text',
              text: JSON.stringify(await WebClient.get(`/api/v1/experiments/${experimentId}`)),
            },
          ],
        };
      },
    );
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves information (implying a read-only operation) but doesn't cover critical aspects like authentication requirements, rate limits, error handling, or response format. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 a single, clear sentence with zero waste. It's front-loaded with the core purpose and efficiently conveys the essential information without unnecessary elaboration, making it highly concise and well-structured.

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 the tool's complexity (a read operation with one parameter), lack of annotations, and no output schema, the description is incomplete. It doesn't address behavioral traits, response details, or usage context, leaving the agent with insufficient information to invoke the tool effectively beyond its basic purpose.

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?

Schema description coverage is 0%, but the description adds minimal semantic context by implying the parameter is an 'experimentId' for a 'specific A/B test experiment'. However, it doesn't explain the parameter's format (e.g., numeric ID), constraints, or examples. With one parameter and low schema coverage, the description provides some value but doesn't fully compensate for the lack of schema details.

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 ('retrieves') and resource ('detailed information for a specific A/B test experiment'), making the purpose unambiguous. It distinguishes from sibling tools like 'experiment-list' by specifying retrieval of details for a single experiment rather than listing multiple. However, it doesn't explicitly contrast with other detail tools (e.g., 'analytics-chart-detail'), so it's not a perfect 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. It doesn't mention prerequisites (e.g., needing an experiment ID), exclusions, or comparisons to sibling tools like 'experiment-list' for listing experiments or other detail tools. Usage is implied by the name and purpose but not explicitly stated.

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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