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Worthune Verified Financial Models

get_household_picture

Read-onlyIdempotent

One household, one picture: the balance sheet by wrapper and owner, income and spending this year, how current the last computation is against the engine's spec (the same drift reasons the weekly scan delivers), the newest decisions, and a data-quality report naming what is missing and what supplying it would unlock. Sums only — no new number of consequence; nothing is stored. Same as GET /api/v1/households/{id}/picture. Pass as_of (YYYY-MM-DD) to pin the date; it is echoed back.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
as_ofNoYYYY-MM-DD or ISO timestamp; default now
api_keyNoWorthune API key (wk_…)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, and the description strongly reinforces and extends this: it explicitly says 'nothing is stored,' 'Sums only — no new number of consequence,' and that as_of is 'echoed back.' It also maps the operation to a GET endpoint. No contradiction with annotations.

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 dense and front-loaded, with most sentences adding substantive information. The parenthetical 'the same drift reasons the weekly scan delivers' is somewhat convoluted and adds marginal value, but overall the description is appropriately sized for the tool's complexity.

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?

For a read-only composite endpoint with no output schema, the description covers the key response sections, the as_of behavior, and the safety profile. It could be slightly clearer about the drift parenthetical and any output format limits, but an agent has enough to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 67%, with as_of and api_key already described. The description adds meaningful semantics for as_of by explaining that passing it 'pins the date' and that it is echoed back. The required id is not described in prose but is clear from the resource context and endpoint path.

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 a specific verb and resource: it produces a composite 'household picture' containing balance sheet by wrapper/owner, income and spending, computation drift, newest decisions, and a data-quality report. This content list makes it unambiguous and distinguishes it from sibling tools like get_household or get_decision.

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 description implies when this tool is useful—when an agent wants a comprehensive one-household snapshot—but it never explicitly says when to use this over alternatives like get_household or list_decisions. There are no exclusion conditions or named alternatives, so usage guidance is only implicit.

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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