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list_datasets

List available datasets for training and evaluation, including those uploaded from S3, to prepare data for fine-tuning or model evaluation.

Instructions

List datasets available for training and evaluation. Datasets can be uploaded from S3 and used for fine-tuning or model evaluation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results (default 20)

Implementation Reference

  • src/mcp.ts:458-468 (registration)
    Registration of the 'list_datasets' MCP tool with name, description, and inputSchema (limit parameter).
    {
      name: "list_datasets",
      description:
        "List datasets available for training and evaluation. Datasets can be uploaded from S3 and used for fine-tuning or model evaluation.",
      inputSchema: {
        type: "object" as const,
        properties: {
          limit: { type: "number", description: "Max results (default 20)" },
        },
      },
    },
  • Handler for 'list_datasets' that calls getClient().listDatasets() with optional limit parameter.
    // --- Datasets ---
    case "list_datasets":
      result = await getClient().listDatasets({
        limit: args?.limit as number | undefined,
      });
      break;
  • API client method listDatasets() that sends a GET request to /api/v1/datasets with optional limit/offset query parameters.
    async listDatasets(options?: {
      limit?: number;
      offset?: number;
    }): Promise<any> {
      const params = new URLSearchParams();
      if (options?.limit) params.set("limit", String(options.limit));
      if (options?.offset) params.set("offset", String(options.offset));
      const qs = params.toString();
      return this.request("GET", `/api/v1/datasets${qs ? `?${qs}` : ""}`);
    }
  • TypeScript type definition for listDatasets options (limit and offset as optional numbers).
    listDatasets(options?: {
        limit?: number;
        offset?: number;
    }): Promise<any>;
Behavior3/5

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

As a read-only listing tool, behavioral transparency is adequate. However, with no annotations, the description could mention side effects or authorization, but the simple nature of listing mitigates this gap.

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

Conciseness3/5

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

The description is concise at two sentences, but the second sentence about S3 uploads is off-topic for a listing tool, slightly reducing relevance.

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?

For a simple list tool with one parameter, the description is mostly complete. However, it doesn't explain the return format or pagination, which is a gap without an output schema.

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 only parameter 'limit' is fully described in the schema (100% coverage). The description adds no extra meaning beyond that, so baseline score is appropriate.

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 that the tool lists datasets for training and evaluation. While it doesn't explicitly differentiate from siblings like 'show_dataset', the name and description make the purpose obvious.

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 is provided on when to use this tool versus alternatives like 'show_dataset' or 'create_dataset'. The second sentence about uploading S3 data is irrelevant to listing.

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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