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Pay-cycle forecast

get_pay_cycle_forecast
Read-only

Raw data: the conditional forecast until next payday, computed from recorded balances and events. Figures only, with no analysis. Use it when the user asks for this detail; a budget question or an overview is answered by get_household_answers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
household_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare read-only/non-destructive, so the safety profile is covered. The description adds real behavioral context beyond them: the output is raw figures with no analysis, and the forecast is conditional and derived from recorded balances and events. It stops short of noting freshness or staleness of the computed forecast.

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 short sentences, front-loaded with the nature of the output ('Raw data:') before the routing guidance. Every sentence earns its place, though the leading 'Raw data' framing is slightly informal.

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?

An output schema exists, so return values needn't be described, and annotations cover safety. The one gap is the undocumented nullable household_id, which matters for correct invocation but is otherwise a complete, well-routed definition.

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

Parameters2/5

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

The single household_id parameter has 0% schema description coverage and a null default, yet the description says nothing about it. It never explains whose household is forecast or what happens when household_id is omitted/null, which is exactly the gap the description should fill.

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 ('the conditional forecast until next payday') and scopes it as computed from recorded balances and events. It also explicitly distinguishes itself from get_household_answers, so an agent can separate the two without opening schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit when-to-use ('when the user asks for this detail') and a when-not with the named alternative ('a budget question or an overview is answered by get_household_answers'). Nothing is left to inference.

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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