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datasets_update

Modify a dataset's name, description, tags, and visibility settings to keep data organized and access controlled.

Instructions

Update dataset metadata — name, description, tags, visibility.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
uuidYesDataset UUID

Implementation Reference

  • src/index.js:53-53 (registration)
    The tool 'datasets_update' is registered in the static tool catalog (STATIC_TOOLS array) with its name, description, and input schema. Its actual handler is not implemented locally; calls are proxied to the remote MCP server via remoteClient.callTool().
    { name: "datasets_update", description: "Update dataset metadata — name, description, tags, visibility.", inputSchema: { type: "object", properties: { uuid: { type: "string", description: "Dataset UUID" } }, required: ["uuid"] } },
  • The input schema for datasets_update requires only a 'uuid' (Dataset UUID) string. Additional metadata fields like name, description, tags, visibility are described in the tool description but not defined in the inputSchema — they may be handled server-side by the remote API.
    { name: "datasets_update", description: "Update dataset metadata — name, description, tags, visibility.", inputSchema: { type: "object", properties: { uuid: { type: "string", description: "Dataset UUID" } }, required: ["uuid"] } },
  • All tool calls (including datasets_update) are handled by a single generic CallToolRequestSchema handler that proxies requests to the remote MCP server. There is no local-specific logic for datasets_update; the actual implementation lives on the remote server.
    server.setRequestHandler(CallToolRequestSchema, async (request) => {
      if (!remoteClient) {
        return {
          content: [
            {
              type: "text",
              text: "MCP Analytics API key required. Set MCP_ANALYTICS_API_KEY in your environment.\nGet a free key at https://app.mcpanalytics.ai",
            },
          ],
          isError: true,
        };
      }
    
      try {
        const result = await remoteClient.callTool({
          name: request.params.name,
          arguments: request.params.arguments || {},
        });
        return result;
      } catch (err) {
        return {
          content: [{ type: "text", text: `Error: ${err.message}` }],
          isError: true,
        };
      }
    });
Behavior2/5

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

With no annotations provided, the description bears full responsibility for behavioral disclosure. It only states 'Update' without detailing side effects, permissions, idempotency, or behavior for unspecified fields. The lack of transparency about the update operation's nature is a significant gap.

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 of 8 words, front-loaded and concise. However, its brevity sacrifices necessary detail, making it too terse for a tool with an incomplete schema.

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

Completeness1/5

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

Given the minimal schema (only uuid) and no output schema, the description must fully explain usage. It fails to specify how to provide the mentioned updatable fields, leaving the agent without critical information to invoke the tool correctly.

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

Parameters1/5

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

The description mentions fields (name, description, tags, visibility) that are not present in the input schema, which only includes 'uuid'. This contradiction misleads the agent into expecting those parameters. The schema coverage is 100% for the single parameter, but the description adds incorrect information, resulting in poor semantics.

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 'Update dataset metadata' and lists specific fields (name, description, tags, visibility), making the tool's action and target clear. However, it does not explicitly differentiate from sibling tools like datasets_read or datasets_upload, though the update action is implied.

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, no prerequisites, and no scenarios for when not to use it. This leaves the agent without context for appropriate usage.

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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