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List dataset runs

listDatasetRuns

Retrieve evaluation runs for a dataset with pagination support. Specify the dataset name to list its rounds, controlling page and limit.

Instructions

List runs (evaluation rounds) for a dataset.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number (default 1)
limitNoItems per page (default 50, max 100)
datasetNameYes

Implementation Reference

  • src/tools.ts:241-253 (registration)
    Registration of the 'listDatasetRuns' tool via server.registerTool() with name, metadata, inputSchema, and handler.
    server.registerTool(
      "listDatasetRuns",
      {
        title: "List dataset runs",
        description: "List runs (evaluation rounds) for a dataset.",
        inputSchema: {
          ...paginationShape,
          datasetName: z.string().min(1),
        },
      },
      async ({ datasetName, ...rest }) =>
        asJson(await client.get(`/api/public/datasets/${enc(datasetName)}/runs`, rest)),
    );
  • Handler function that calls the Langfuse API: GET /api/public/datasets/{datasetName}/runs with pagination params.
      async ({ datasetName, ...rest }) =>
        asJson(await client.get(`/api/public/datasets/${enc(datasetName)}/runs`, rest)),
    );
  • Input schema requiring datasetName (string) and paginationShape (page, limit).
    inputSchema: {
      ...paginationShape,
      datasetName: z.string().min(1),
    },
  • src/tools.ts:409-420 (registration)
    Tool name listed in the TOOL_NAMES const array for enumeration purposes.
      "listDatasetRuns",
      "getDatasetRun",
      "getMetrics",
      "getDailyMetrics",
      "listModels",
      "getModel",
      "listProjects",
      "listComments",
      "getComment",
      "getMedia",
      "getHealth",
    ] as const;
  • paginationShape helper schema imported by listDatasetRuns input schema, defining page and limit fields.
    export const paginationShape = {
      page: z.number().int().positive().optional().describe("Page number (default 1)"),
      limit: z
        .number()
        .int()
        .min(1)
        .max(100)
        .optional()
        .describe("Items per page (default 50, max 100)"),
    };
Behavior2/5

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

With no annotations, the description fails to disclose pagination behavior, error handling, or authentication needs. The single sentence adds no behavioral context beyond the tool's name.

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 sentence, very concise with no redundancy. It could benefit from more detail, but for a simple list tool, it is appropriately sized.

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?

No output schema is provided, and the description gives no indication of the response format (e.g., list of run objects). While the tool is simple, the description lacks essential context for an agent to use it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool description adds no meaning beyond the input schema. The required 'datasetName' parameter lacks a description in both schema and description, and the 67% schema coverage is not compensated.

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 verb ('List'), the resource ('runs'), and the scope ('for a dataset'). It distinguishes from siblings like 'listDatasets' and 'getDatasetRun' effectively.

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?

No guidance on when to use this tool vs alternatives like 'getDatasetRun'. No exclusions or context provided beyond the basic purpose.

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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