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ynab_get_month

Read-onlyIdempotent

Fetch comprehensive budget data for a specific month, including category balances, income, and activity, to analyze your financial performance.

Instructions

Get full budget data for a specific month including all category balances.

Args:

  • budget_id (string, optional): Budget UUID. Omit to use the default budget.

  • month (string, required): Month in YYYY-MM-DD format (use first day, e.g. "2025-01-01").

  • response_format (string, optional): "json" or "markdown" (default: "markdown").

Returns: month (month, income, budgeted, activity, to_be_budgeted, age_of_money, categories[]), cached, cache_info

Examples:

  • Get January 2025: set month="2025-01-01"

Errors:

  • "No default budget set" → run ynab_set_default_budget first

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
budget_idNo
monthYes
response_formatNomarkdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
cachedNoIndicates if data was served from cache
cache_infoNoHuman-readable cache status message (e.g., "Cache hit", "Cache miss")
usedDeltaNoIndicates if delta merge optimization was applied for budgets
monthYesMonth details
Behavior4/5

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

Annotations already indicate readOnly, idempotent, non-destructive. The description adds value by mentioning that results are cached (returning 'cached' and 'cache_info') and that omitting budget_id uses the default budget. No contradictions 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with Args, Returns, Examples, Errors sections. It is concise, front-loaded with the purpose, and every sentence adds value without redundancy.

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?

Given an output schema exists (not shown but referenced), the description adequately covers parameter details, return fields summary, and a common error. It is complete for a read-only data retrieval tool.

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

Parameters5/5

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

With 0% schema description coverage, the description fully explains all parameters: budget_id is optional (defaults), month is required (YYYY-MM-DD format, use first day), response_format has enum values and default. Example clarifies usage.

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 retrieves full budget data for a specific month including all category balances. This distinguishes it from sibling tools like ynab_list_months (which lists months) and ynab_get_budget (which gets overall budget).

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?

The description provides a clear context: when you need a month's full data, including categories. It includes an error case (no default budget) and example usage, but does not explicitly list alternative tools for when a simpler lookup (e.g., get_category) suffices.

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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