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analytics_breakdown

Read-only

Aggregate KPIs broken down by one dimension: product_type, sales_channel, fulfillment_provider, product, variant, or hold_reason. Rows are sorted for display; overflow past the limit folds into an "(everything else)" row so totals still reconcile. Requires an Advanced Analytics plan. Read-only.

[#127113]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNoEnd date (YYYY-MM-DD). Omit to default to today (UTC).
limitNoMax rows before folding the rest into "(everything else)" (default 50).
startNoStart date (YYYY-MM-DD). Omit to default to 30 days before end.
storeNoStore uuid to narrow to one store. Omit for all accessible stores.
currencyNoReporting currency (e.g. "USD"). Currencies are segmented, never summed.
dimensionYesThe dimension to break down by (required).
workspaceNoWorkspace uuid to scope to (agency accounts). Omit for the Default workspace.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already cover readOnlyHint=true, so the trailing "Read-only" adds nothing. The description does earn credit for two non-annotation facts: the Advanced Analytics plan gate and the "(everything else)" folding behavior that keeps totals reconciling. It still omits how long a large breakdown takes or any rate-limit/auth nuance.

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?

Three tight sentences, front-loaded with the core action and scope, with no filler. The stray "[#127113]" artifact is dead weight but minor.

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

Completeness4/5

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

With no output schema, the description covers what an agent needs: scope (one dimension), the row-cap/folding semantics, the plan prerequisite, and read-only nature. It stops short of explaining reconciliation output fields or currency segmentation, though the schema's currency description partially covers the latter.

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 100%, so all 7 parameters (dates, limit, store, currency, dimension, workspace) are already documented in the schema with defaults and constraints. The description restates the dimension options already present in the enum and the limit-folding behavior already noted on the limit param, adding no new parameter meaning. Baseline 3 is correct.

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 verb+resource ("Aggregate KPIs") and enumerates the exact dimensions it can break down by, which distinguishes it from a by-time tool. It never names the analytics siblings (summary/timeseries/portfolio), so an agent must infer the split from the phrase "broken down by one dimension" rather than being told.

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?

It supplies one hard prerequisite ("Requires an Advanced Analytics plan") which is genuinely useful for routing. However, it gives no explicit when-to-use guidance against analytics_summary, analytics_timeseries, or analytics_portfolio, leaving the agent to infer usage from the dimension phrasing alone.

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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