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get_profitability

Calculate net profitability per ASIN by subtracting FBA fees, referral fees, ad spend, COGS, and returns from gross sales.

Instructions

Read net profitability by ASIN: gross sales minus FBA fees, referral fees, ad spend, COGS, and returns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
start_dateNoStart of the date range, YYYY-MM-DD.
end_dateNoEnd of the date range, YYYY-MM-DD.

Implementation Reference

  • src/index.ts:172-177 (registration)
    Tool registration for 'get_profitability' in the tools array. Defines name, description, and inputSchema (dateRangeSchema). No local handler exists — this is a stub that returns a hosted-service notice.
    {
      name: "get_profitability",
      description:
        "Read net profitability by ASIN: gross sales minus FBA fees, referral fees, ad spend, COGS, and returns.",
      inputSchema: dateRangeSchema,
    },
  • The dateRangeSchema used as input schema for get_profitability. Expects start_date and end_date with YYYY-MM-DD format.
    const dateRangeSchema = {
      type: "object" as const,
      properties: {
        start_date: {
          type: "string",
          format: "date",
          description: "Start of the date range, YYYY-MM-DD.",
        },
        end_date: {
          type: "string",
          format: "date",
          description: "End of the date range, YYYY-MM-DD.",
        },
      },
      additionalProperties: false,
    }
  • The CallToolRequestSchema handler. For 'get_profitability' (and all tools except 'agentcentral_setup'), it returns a stub notice directing users to the hosted endpoint. The actual profitability logic executes server-side on the remote MCP server.
    server.setRequestHandler(CallToolRequestSchema, async (request) => {
      const name = request.params.name
      if (name === "agentcentral_setup") {
        return {
          content: [
            {
              type: "text",
              text:
                `Hosted MCP endpoint:\n  ${HOSTED_URL}\n\n` +
                `Setup guide:\n  ${SETUP_URL}\n\n` +
                `Add this to your client config:\n` +
                `{\n  "mcpServers": {\n    "agentcentral": {\n      "url": "${HOSTED_URL}",\n      "headers": { "Authorization": "Bearer ac_live_<YOUR_API_KEY>" }\n    }\n  }\n}`,
            },
          ],
          isError: false,
        }
      }
      return {
        content: [
          {
            type: "text",
            text: HOSTED_NOTICE,
          },
        ],
        isError: false,
      }
    })
Behavior3/5

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

With no annotations, the description reveals it is a read operation and lists components, but it fails to disclose rate limits, authentication needs, data recency, or limitations. The behavioral disclosure is adequate but not comprehensive.

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?

The description is a single, efficient sentence that front-loads the key action and scope. No unnecessary words.

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?

The description claims profitability 'by ASIN', but the input schema lacks an ASIN parameter. This mismatch undermines completeness. Additionally, no output schema or behavioral context beyond the formula is provided.

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. The description does not add parameter-level details beyond the schema, so the baseline of 3 is appropriate.

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 tool reads net profitability by ASIN and specifies the formula (gross sales minus various costs). It distinguishes itself from sibling tools that focus on campaigns, budgets, or inventory.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for profitability data but provides no guidance on when to use this tool versus alternatives like get_fee_breakdown or get_settlement_economics. No when-not or prerequisites are mentioned.

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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