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nadine302324-commits

Lexicon Intelligence

lexicon_monitor_refunds

Monitor refund rate and customer satisfaction signals for a specific vendor to identify trends and improve retention.

Instructions

Refund rate and customer satisfaction signal monitoring for a vendor.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
vendorYesVendor name
industryNoIndustry context

Implementation Reference

  • index.js:59-70 (registration)
    Registration (definition) of the 'lexicon_monitor_refunds' tool in the TOOLS array, including its name, description, and inputSchema (requires 'vendor', optional 'industry').
    {
      name: "lexicon_monitor_refunds",
      description: "Refund rate and customer satisfaction signal monitoring for a vendor.",
      inputSchema: {
        type: "object",
        properties: {
          vendor:   { type: "string", description: "Vendor name" },
          industry: { type: "string", description: "Industry context" },
        },
        required: ["vendor"],
      },
    },
  • index.js:85-92 (registration)
    Mapping from the local tool name 'lexicon_monitor_refunds' to the remote endpoint 'lexicon.monitor.refunds' in the TOOL_MAP object.
    const TOOL_MAP = {
      lexicon_compare_vs:          "lexicon.compare.vs",
      lexicon_compare_methodology: "lexicon.compare.methodology",
      lexicon_compare_topic:       "lexicon.compare.topic",
      lexicon_monitor_outage:      "lexicon.monitor.outage",
      lexicon_monitor_refunds:     "lexicon.monitor.refunds",
      lexicon_feed:                "lexicon.feed",
    };
  • Generic CallToolRequestSchema handler that receives 'lexicon_monitor_refunds', looks up the remote tool name, forwards the request via fetch to the remote MCP endpoint, and returns the response.
    server.setRequestHandler(CallToolRequestSchema, async (request) => {
      const { name, arguments: args } = request.params;
      const remoteTool = TOOL_MAP[name];
      if (!remoteTool) {
        return { content: [{ type: "text", text: `Unknown tool: ${name}` }], isError: true };
      }
    
      const headers = { "Content-Type": "application/json" };
      if (API_KEY) headers["X-API-Key"] = API_KEY;
    
      const response = await fetch(`${BASE_URL}/mcp/v1`, {
        method: "POST",
        headers,
        body: JSON.stringify({
          jsonrpc: "2.0",
          id: 1,
          method: "tools/call",
          params: { name: remoteTool, arguments: args },
        }),
      });
    
      const data = await response.json();
      if (data.result) return data.result;
      return {
        content: [{ type: "text", text: JSON.stringify(data.error || data) }],
        isError: true,
      };
    });
Behavior2/5

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

No annotations are provided, and the description does not disclose behavioral details such as side effects, permissions, or data scoping. For a monitoring tool, it is unclear if it is read-only or requires special access. The description minimally implies passive observation but fails to offer transparency.

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?

Single sentence that is front-loaded with the core action and resource. No wasted words; the sentence is appropriately sized for the tool's simplicity.

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 does not explain what the monitoring outputs look like (e.g., refund rate values, satisfaction signals format). For a monitoring tool, this is a significant omission that hinders an agent from understanding the return value.

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 coverage is 100%, with descriptions for both parameters (vendor and industry). The description restates 'for a vendor' but adds no extra meaning beyond the schema. Baseline 3 is appropriate as the schema already documents the parameters well.

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 tool monitors refund rate and customer satisfaction signals for a vendor, distinguishing it from sibling tools like lexicon_monitor_outage which monitors outages. The verb 'monitoring' is specific enough, and the resource is well-defined.

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 versus alternatives. It does not specify conditions for use, prerequisites, or cases where another tool like lexicon_feed might be more appropriate. The description lacks explicit usage context.

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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