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update_transactions

Idempotent

Modify multiple YNAB transactions in one batch operation with validation, cache management, and optional metadata for efficient updates.

Instructions

Update multiple transactions in a single batch (1-100 items) with dry-run validation, automatic cache invalidation, and response size management. Supports optional original_account_id and original_date metadata for efficient cache invalidation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
budget_idYes
transactionsYes
dry_runNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

The description adds valuable behavioral context beyond annotations: it specifies batch size limits (1-100 items), mentions dry-run validation capability, automatic cache invalidation, and response size management. While annotations cover idempotency and non-destructive nature, the description provides practical implementation details that help the agent understand runtime behavior.

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 perfectly concise with two well-structured sentences. The first sentence establishes core functionality with key features, and the second adds specific parameter context. Every word earns its place with no redundancy or wasted verbiage.

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?

Given the tool's complexity (batch updates with 3 parameters, nested transaction objects), the description provides good context about batch behavior and cache management. With annotations covering safety aspects and an output schema presumably handling return values, the main gap is lack of guidance on when to use this versus single-transaction updates.

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?

With 0% schema description coverage, the description compensates by explaining the purpose of 'original_account_id' and 'original_date' parameters for 'efficient cache invalidation'. It also implies the 'dry_run' parameter's function through 'dry-run validation'. However, it doesn't cover all 3 top-level parameters or explain the transaction object structure.

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 the specific action ('Update multiple transactions in a single batch'), resource ('transactions'), and scope ('1-100 items'), distinguishing it from the sibling 'update_transaction' which handles single transactions. It provides precise operational boundaries that help the agent understand this is a batch operation.

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 implies usage context through 'batch (1-100 items)' and mentions 'dry-run validation' as an option, suggesting when to use this for efficiency. However, it doesn't explicitly state when to choose this over 'update_transaction' or other sibling tools like 'create_transactions', leaving some guidance implicit rather than explicit.

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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