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avenir-mcp

Category balances for a month

get_category_balances
Read-onlyIdempotent

Fetch every visible category's budgeted, spent and available amounts for a specified month to reveal what remains and highlight possible overspending.

Instructions

Budgeted, spent (activity) and available (balance) per category for a month.

Use it for "how much is left in Groceries?" or to list every category's money. Amounts in currency units; activity is negative for spending. Hidden and internal categories are left out, and so are categories with nothing budgeted, spent or available unless include_empty is true. For the share of each budget consumed use get_budget_vs_actual; for the month's totals, get_monthly_summary. One YNAB request; changes nothing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
monthNo'YYYY-MM-01' or 'current'.current
plan_idYesYNAB plan id or 'last-used'.
include_emptyNoAlso list categories with no amount at all.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, it discloses the exclusion rules (hidden and internal categories dropped; empty categories omitted unless include_empty is true), the currency-unit and sign convention (activity negative for spending), and the cost profile (one YNAB request, no mutation). This is meaningful behavioral context an agent could not derive from the annotations alone.

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 usage, alternatives, and behavioral constraints in a tight block. The closing "One YNAB request; changes nothing" is mildly redundant with readOnlyHint, but the rest earns its place.

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?

An output schema exists, so return shape need not be explained. Purpose, usage routing, exclusion semantics, and safety profile are all covered, leaving no gap an agent needs to fill before invoking the tool.

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 coverage is 100%, so the schema already documents month, plan_id, and include_empty. The description adds real meaning on top: the default behavior of excluding categories with no budgeted/spent/available amount, and the hidden/internal exclusion rule that is not in the schema. That is more than a restatement.

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 opening sentence states a specific verb-set and resource: budgeted, spent (activity), and available (balance) per category for a month. It is immediately distinguishable from siblings like get_budget_vs_actual and get_monthly_summary, which are named explicitly later.

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?

It gives concrete user-intent triggers ("how much is left in Groceries?", "list every category's money") and points to two named alternatives with the condition that selects them. Explicit when-to-use and when-to-use-something-else guidance is present.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.