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by ai.nuira
OverviewDiscussionsAdmin

Storefront funnel

get_storefront_funnel
Read-onlyIdempotent

The web's funnel from Shopify's sessions, in total and on mobile and desktop, against the comparison period: sessions, purchases, and each step's rate in both (addToCart, cartToCheckout, checkoutToPurchase, conversion; changePoints already in points), with stepThatFellMost. A previous figure of null means no sessions recorded then, not zero. byPageType is the current period per kind of landing page. sessionsByChannel is GA4's sessions per traffic channel in both periods, empty with no GA4: use it for where traffic came from, as its total differs from Shopify's. Use for conversion by device, where visitors drop off and where the traffic came from. Optional from and to (inclusive YYYY-MM-DD, both or neither, never after today) read another span instead of the default period. A named month, a week or two dates the operator gave MUST be sent here: without them this reads the last 30 days, which is not that month.

Input Schema

NameRequiredDescriptionDefault
toNoLast day of the span, inclusive, as YYYY-MM-DD; not after today. Send together with `from`, or omit both to read the default 30-day period.
fromNoFirst day of the span, inclusive, as YYYY-MM-DD. Send together with `to`, or omit both to read the default 30-day period.
compareNoWhat to compare the span with: previous (default, the same number of days just before), yoy (the same dates last year) or yoyWeekday (52 weeks back, the same weekdays — use it for natural Monday–Sunday weeks or whenever the operator says 'last year' over weeks).
compareToNoLast day of the named comparison period, YYYY-MM-DD.
compareFromNoFirst day of a NAMED comparison period, YYYY-MM-DD, with compareTo. For 'September with October': from/to October, compareFrom/compareTo the whole of September. Takes the place of compare.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / properties / compare
      Added value: +{
+  "description": "What to compare the span with: previous (default, the same number of days just before), yoy (the same dates last year) or yoyWeekday (52 weeks back, the same weekdays — use it for natural Monday–Sunday weeks or whenever the operator says 'last year' over weeks).",
+  "enum": [
+    "previous",
+    "yoy",
+    "yoyWeekday"
+  ],
+  "type": "string"
+}
    • addedInput schema / properties / compareFrom
      Added value: +{
+  "description": "First day of a NAMED comparison period, YYYY-MM-DD, with compareTo. For 'September with October': from/to October, compareFrom/compareTo the whole of September. Takes the place of compare.",
+  "format": "date",
+  "type": "string"
+}
    • addedInput schema / properties / compareTo
      Added value: +{
+  "description": "Last day of the named comparison period, YYYY-MM-DD.",
+  "format": "date",
+  "type": "string"
+}
  2. Added

TDQS

A4.1/5.0
Behavior5/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), and the description adds substantial behavior on top: null means no sessions were recorded rather than zero, changePoints are expressed in points, sessionsByChannel is empty without GA4 and its total deliberately differs from Shopify's, and byPageType is current-period only. These are exactly the quirks that would otherwise cause misreading of results.

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?

Purpose and metric inventory are front-loaded and there is no filler — every clause carries information about outputs or date handling. The first sentence is however a very dense run-on with nested parentheses, which costs some readability even though nothing is wasted.

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?

There is no output schema, so the description carries the burden of describing returns, and it does so thoroughly: each metric group, change-point units, null semantics, empty-GA4 behavior, and the current-period-only scope of byPageType. Combined with the complete input schema and annotations, an agent has everything needed to call and interpret it.

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% and each parameter is documented there, including the from/to pairing rule, the compare enum meanings, and compareFrom/compareTo replacing compare. The description mostly restates those constraints (both or neither, never after today, 30-day default) rather than adding format or interpretation detail beyond the schema, so the baseline 3 applies.

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?

States a specific resource (Shopify web sessions funnel) plus the exact measures returned — sessions, purchases, addToCart/cartToCheckout/checkoutToPurchase/conversion rates, stepThatFellMost — and the splits (total, mobile, desktop, byPageType, sessionsByChannel). It does not name a sibling it differs from, so an agent must infer the boundary against tools like get_sales_breakdown or get_channels, which keeps it at 4 rather than 5.

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?

Gives concrete use cases ('Use for conversion by device, where visitors drop off and where the traffic came from') and a strong conditional rule: a named month, week or two dates the operator supplied MUST be sent as from/to because the default is the last 30 days. It lacks explicit when-not guidance or named alternative tools, so it falls short of 5.

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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