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Spending by category

spending_by_category
Read-only

Total spending per category for a period, with the change versus the preceding period of equal length. Spending is attributed consumption, net of refunds; internal transfers between the user's own accounts are matched and excluded, and flows that can't be attributed on a single connected bank are set aside as "money moved" (see income_and_savings) rather than counted as spending. Positive figures = money spent. Every answer states the date the data is current as at.

Input Schema

NameRequiredDescriptionDefault
newest-timeNoInclusive end of the period, ISO 8601 date or date-time (e.g. 2026-05-31). Defaults to the most recent data.
oldest-timeNoInclusive start of the period, ISO 8601 date or date-time (e.g. 2026-05-01). Defaults to 90 days before the end of the period, or the start of available data if there is less than that. Pass this explicitly to ask about the household's full history.

Output Schema

NameRequiredDescriptionDefault
noteNo
periodNo
categoriesNo
totalSpentNo
dataCoverageNo
previousPeriodNo
previousPeriodTotalSpentNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior5/5

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

Annotations cover the safety profile (readOnly, non-destructive). The description adds substantial beyond structured data: how spending is attributed (consumption, net of refunds), internal transfers are matched and excluded, unattributable flows are set aside as 'money moved', sign convention (positive = money spent), and data currency disclosure. This is rich behavioral context an agent needs.

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?

Front-loaded with the core purpose, then method details. Each sentence earns its place. Slightly dense but no waste; the parenthetical cross-reference and final sentence about data currency are valuable.

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?

Complete for a read-only analytical tool with an output schema. The description explains the attribution model, exclusions, sign convention, and data freshness, covering what an agent needs to interpret and trust the results. Output schema handles return structure.

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%, so the schema already documents both parameters thoroughly, including defaults and semantics. The description adds no parameter-specific information beyond what the schema provides. Baseline 3 when schema does the heavy lifting.

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?

States a specific verb+resource ('Total spending per category for a period') with the added comparative dimension (change vs preceding equal-length period). This is distinct from siblings like top_merchants (merchant-level) and income_and_expenditure. An agent can identify the tool unambiguously.

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?

Implied usage is clear from the purpose, but no explicit when-to-use vs alternatives guidance. The description mentions income_and_savings for 'money moved' but does not route the agent to top_merchants, monthly_trend, or income_and_expenditure. Adequate but with gaps.

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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