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lindoai

mcp-lindoai

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get_workspace_analytics

Read-only

Retrieve workspace analytics to monitor the performance of AI-generated websites, pages, and blog posts.

Instructions

Get workspace analytics.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Registration of the 'get_workspace_analytics' tool. No inputs, returns workspace analytics data from the API endpoint /v1/workspace/analytics.
    server.tool(
      "get_workspace_analytics",
      "Get workspace analytics.",
      {},
      { title: "Get Workspace Analytics", readOnlyHint: true, destructiveHint: false, openWorldHint: false },
      async () => {
        const data = await apiCall("/v1/workspace/analytics", "GET");
        return { content: [{ type: "text", text: JSON.stringify(data, null, 2) }] };
      }
    );
  • Handler function for get_workspace_analytics. Makes a GET request to /v1/workspace/analytics and returns the JSON response as text content.
    async () => {
      const data = await apiCall("/v1/workspace/analytics", "GET");
      return { content: [{ type: "text", text: JSON.stringify(data, null, 2) }] };
    }
  • Helper function that performs the actual HTTP API call to the Lindo AI backend with the configured API key.
    async function apiCall(path, method, body) {
      const url = `${BASE_URL}${path}`;
      const res = await fetch(url, {
        method,
        headers: {
          Authorization: `Bearer ${API_KEY}`,
          "Content-Type": "application/json",
        },
        ...(body ? { body: JSON.stringify(body) } : {}),
      });
      return res.json();
    }
Behavior2/5

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

Annotations indicate readOnlyHint=true and destructiveHint=false, but the description adds no additional behavioral context (e.g., what analytics are aggregated, time range, or permissions). The description fails to build on the annotations.

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 extremely concise at four words, but it sacrifices informativeness. Every word is earned, but the agent still lacks actionable detail.

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?

With no output schema and a sparse description, the agent cannot infer return values or scope of 'analytics'. Given 32 sibling tools, the description is insufficient for correct tool selection.

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

Parameters4/5

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

The input schema has zero parameters, so no parameter documentation is needed. The description correctly implies no inputs, earning the baseline score of 4.

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 'Get' and resource 'workspace analytics', making the purpose evident. However, there is no differentiation from the sibling tool 'get_website_analytics', which could confuse an agent.

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 'get_website_analytics' or 'get_credits'. The agent receives no context about applicable scenarios.

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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