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Caribooks (QuickBooks Online)

get customer sales

get_customer_sales
Read-only

Generate the QuickBooks customer sales report. Returns { columns, column_types, rows }: each row has a type (section | data | total), a depth, and values aligned to columns (Money cells as numbers, first cell is the label on summary reports); id is the label cell's QuickBooks record id (e.g. the account); on detail reports ids aligns to values instead. All-zero rows are omitted and counted in hidden_zero_rows. filters lists the filters QuickBooks confirms it applied (a parameter it ignored is absent), and no_data: true means the period has nothing to report.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsNoQuickBooks report query parameters: start_date, end_date (YYYY-MM-DD) or date_macro (Today, Yesterday, This Week, Last Week, This Month, Last Month, This Month-to-date, This Fiscal Quarter, Last Fiscal Quarter, This Fiscal Year, Last Fiscal Year, This Fiscal Year-to-date, Last Fiscal Year-to-date, ...); accounting_method (Cash|Accrual); summarize_column_by (Total|Month|Quarter|Year|Week|Days|Classes|Departments|Customers|Vendors|Employees|ProductsAndServices); the filters customer, vendor, item, class, department (QuickBooks Ids, comma-separated for several).
companyNoWhich connected QuickBooks company to use (name, realm id, or connection id). Optional when only one company is connected.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations indicate read-only and non-destructive, and the description adds valuable behavioral details: it explains the output format, handling of zero rows, and the semantics of filters and no_data flag. It goes beyond annotations by clarifying the shape of the response and edge cases, which is crucial for understanding tool behavior.

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?

The description is detailed but extremely dense, packing a lot of information into a few sentences. It's structured and front-loads the main purpose, but the output format explanation is lengthy and might be considered as lacking in readability, though still efficient for the technical audience.

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?

Given the complexity of the tool and the lack of an output schema, the description does an admirable job explaining the return format, including the role of each field and edge cases. The output schema is absent, so the description compensates fully; the only minor omission is examples of date_macro values, but the ellipsis implies more.

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 covers 100% of parameters with descriptions, so baseline is 3. The description adds context about filters (that unconfirmed filters are absent), but the schema already explains the parameters and their types. The description reinforces the filter behavior but doesn't introduce new parameter details beyond that.

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?

The description clearly states it generates the QuickBooks customer sales report, a specific verb and resource. It distinguishes itself from siblings by specifying the report type and providing detailed output structure, which sets it apart from other get_* reports.

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?

While it doesn't explicitly say when not to use it or name alternative tools, the description clearly implies it's for customer sales reports, and the sibling list includes related tools like get_customer_income or get_item_sales, suggesting an agent can infer usage. It provides report-specific details but lacks explicit exclusions.

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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