Maple Voice AI

Estimate order sales lost to missed calls

estimate_missed_call_revenue

Read-onlyIdempotent

Use only when the user supplies their own call volume and asks what missed phone calls may cost a restaurant. Runs the same model as the maple.inc ROI calculator on the numbers given: calls per day, the share missed and average order value, plus optional assumptions that otherwise use the calculator's illustrative defaults. Returns an illustrative estimate of order sales from missed calls with every assumption shown. It is a scenario, not a measured result or a guarantee, and it leaves out reservations and catering. Read-only arithmetic.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "callsPerDay": "<callsPerDay>",
      "missedCallPercent": "<missedCallPercent>",
      "averageOrderValue": "<averageOrderValue>"
    },
    "name": "estimate_missed_call_revenue"
  }
}

Input Schema

Name	Required	Description
`callsPerDay`	Yes	Inbound phone calls per day.
`orderCallPercent`	No	Share of missed calls that were order requests. Default 50.
`averageOrderValue`	Yes	Average phone order value in dollars.
`missedCallPercent`	Yes	Share of calls that go unanswered, 0-100.
`capturedOrderPercent`	No	Share of those order requests that would become completed orders. Default 50.
`operatingDaysPerMonth`	No	Days open per month. Default 30.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 11, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations already cover readOnly/idempotent/non-destructive, but the description adds the behavior that actually matters here: optional inputs silently fall back to the calculator's illustrative defaults, assumptions are echoed in the output, the result is a scenario rather than a measurement or guarantee, and reservations and catering are out of scope. Those are real usage-shaping facts an agent cannot get from the annotation block.

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?

Front-loads the gating condition, then the model, then the output and caveats — a sensible order with no filler. Minor redundancy between 'It is a scenario, not a measured result or a guarantee' and the trailing 'Read-only arithmetic,' which restates the annotation hint.

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

Completeness5/5

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

With no output schema, the description still says what comes back ('an illustrative estimate of order sales from missed calls with every assumption shown') and flags the scope limits. For a pure-arithmetic tool with six fully documented parameters, nothing an agent needs in order to call it correctly is missing.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds value beyond the schema: it identifies which inputs are the core three (calls per day, share missed, average order value) and characterizes the remaining ones as 'optional assumptions' drawn from the calculator's defaults, telling the agent they can be omitted deliberately rather than by accident.

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?

States a specific verb and resource ('Estimate order sales lost to missed calls') and names the exact model it replicates (the maple.inc ROI calculator). This clearly separates it from the sibling lookup tools like get_pricing or check_restaurant_systems, which retrieve information rather than compute a scenario.

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

Usage Guidelines4/5

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

'Use only when the user supplies their own call volume and asks what missed phone calls may cost a restaurant' gives an explicit precondition and an implicit exclusion (don't use it when the user has no numbers). It stops short of naming what to do instead in that case, so it is strong but not a full routing instruction.

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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