twelvebit Analytics

Paid sales by customer type and order source

get_paid_sales

Read-onlyIdempotent

Paid orders, refunds and net sales grouped by Shopify customer type and order source. Includes orders without website visits. Historical classification uses current customer tags; customer type is independent of checkout source. These filters do not classify website visitors or funnels.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_paid_sales"
  }
}

Input Schema

Name	Required	Description
`to`	No	Last day, inclusive (YYYY-MM-DD).
`from`	No	First day (YYYY-MM-DD, site time zone). Use with to instead of period.
`site`	No	Site domain (example.com), id or public id (tb_…). Optional with a site key, or when the account has one site.
`period`	No	Time range. Default 30d. today, yesterday, 24h, 7d, 30d, 90d, 12m, wtd, mtd, ytd, all.
`order_source`	No
`customer_type`	No

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 23, 2026

TDQS

A3.5/5.0

Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive, so that bar is covered. The description adds genuinely useful data semantics — orders without website visits are included, historical classification uses current customer tags — but says nothing about response shape, row counts, or how refunds are netted.

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 metrics returned and the grouping dimensions. The trailing exclusion sentence is compressed to the point of being slightly cryptic, but nothing is wasted.

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 does the necessary work of enumerating the returned measures (paid orders, refunds, net sales) and the two grouping dimensions. Remaining gaps are around enum value meaning and response shape, which are modest for a read-only reporting endpoint.

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 67%, with three enum params (order_source, customer_type, period) that carry no inline descriptions. The description explains the concept of customer_type classification but never maps its enum values (wholesale/distributor/d2c/unknown) or clarifies order_source. Baseline 3 given partial schema coverage.

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: paid orders, refunds and net sales grouped by Shopify customer type and order source. The grouping dimensions distinguish it from generic siblings like get_revenue or get_breakdown, though no sibling is named explicitly.

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 closing line 'These filters do not classify website visitors or funnels' implies a boundary against funnel/visitor tools, but no positive guidance on when to choose this over get_revenue or get_breakdown is given. Usage is inferred rather than stated.

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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