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upGrowth Growth Toolkit

Ecommerce metrics (AOV, conversion rate, revenue per visitor)

ecommerce_metrics
Read-onlyIdempotent

Calculates average order value, conversion rate, revenue per visitor and orders per customer, and the sessions needed to hit a revenue target.

Input Schema

NameRequiredDescriptionDefault
ordersYes
revenueYes
currencyNoISO currency code for display, for example INR, USD or AED. Defaults to INR.INR
sessionsNoOptional sessions or visitors in the same period.
customersNoOptional unique customers.
target_revenueNoOptional revenue goal for the same period length.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered. The description adds that it performs calculations and can derive sessions needed for a revenue target, but it does not explain how optional inputs affect the result or what happens when sessions/customers are omitted.

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, front-loaded sentence that enumerates the metrics without filler. Every phrase contributes to identifying the calculation outputs.

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

Completeness3/5

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

This is a calculation tool with six parameters, no output schema, and only partial parameter documentation in the description. It names the metrics but does not explain return shape, edge cases, or how optional parameters change the available outputs, leaving meaningful gaps for an agent to infer.

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 description coverage is moderate at 67%, with currency, sessions, customers, and target_revenue documented while revenue and orders rely on their names and required status. The description adds some meaning by mentioning the sessions-to-target calculation, but it does not map parameters to specific metrics or clarify the effect of optional inputs.

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 states a specific verb (calculates) and enumerates concrete ecommerce metrics, so the tool's purpose is clear. It does not explicitly distinguish itself from related siblings such as unit_economics or break_even, which prevents a 5.

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, when not to use it, or which sibling tool to choose instead. It only lists what is calculated, leaving usage context entirely implicit.

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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