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get_transactions_tool

Retrieve and filter bank transaction data by date, account, category, merchant, or amount range for financial analysis.

Instructions

Query cached transactions. Dates are YYYY-MM-DD. Run sync_transactions first to refresh. Positive amounts = spend.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
start_dateYes
end_dateYes
account_idNo
categoryNo
merchantNo
min_amountNo
max_amountNo
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries full burden. It discloses key behavioral traits: the data is cached (implying potential staleness), requires prior sync for freshness, and clarifies amount semantics ('Positive amounts = spend'). However, it doesn't mention pagination behavior, rate limits, error conditions, or authentication requirements.

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?

Three concise sentences with zero waste. First establishes purpose, second provides date format and prerequisite, third clarifies amount semantics. Each sentence earns its place by adding distinct, valuable information.

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 8 parameters with 0% schema coverage, no annotations, but an output schema exists, the description provides adequate context. It covers the core purpose, prerequisite, date format, and amount interpretation. The output schema handles return values, so the description focuses on usage context appropriately.

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 0%, so the description must compensate. It adds crucial semantic context: date format ('YYYY-MM-DD'), amount interpretation ('Positive amounts = spend'), and implies filtering capabilities. While it doesn't detail all 8 parameters individually, it provides enough guidance for effective use given the output schema exists.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Query cached transactions' specifies both the verb (query) and resource (cached transactions). It distinguishes from siblings like 'search_transactions_tool' by emphasizing the 'cached' aspect, though it doesn't explicitly contrast with all similar tools.

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 clear usage guidance: 'Run sync_transactions first to refresh' indicates a prerequisite. It distinguishes from 'sync_transactions_tool' by positioning this as a query tool for cached data, though it doesn't explicitly state when NOT to use it or compare with 'search_transactions_tool'.

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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