get_transactions_for_period

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

No annotations are provided, so the description must fully disclose behavior. It only states the purpose and parameter sources, but does not mention response format, read-only nature, potential side effects, pagination, error handling, or whether the date range is inclusive. For a read operation, this lack of transparency about the return value and boundaries leaves the agent guessing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is a standard docstring with a clear first sentence followed by an Args list. It is appropriately sized with no fluff, but the Args section is somewhat verbose for a simple lookup. Still, every line earns its place by providing necessary parameter semantics, so it is well-structured and easy to scan.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 4 required parameters, no enums, and an output schema is present (so return values are externally defined). The description covers the essential context: what the tool does, where parameters come from, and the date format. It lacks any behavioral notes like whether the end date is inclusive or how results are ordered, but given the output schema, the description is largely complete for a data-fetching tool.

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

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

The input schema shows 0% description coverage, and the description compensates exceptionally by explaining each parameter in the Args section, including the required format for start_date/end_date (YYYY-MM-DD) and the source tools for session and account_id. This goes beyond the bare schema and gives the agent actionable meaning for all four parameters.

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

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

The description opens with a clear, specific statement: 'Get transactions for an account between two dates.' This identifies the verb (get), resource (transactions), and scope (account, date range), distinguishing it from the sibling tool 'get_transactions' which likely covers all or single-date transactions. The purpose is unambiguous and directly tied to the function name.

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

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

The Args section provides usage guidance by explicitly telling the user that 'session' comes from list_sessions and 'account_id' comes from list_accounts, implying a sequence of prerequisite calls. This clarifies when this tool is appropriate (after listing sessions and accounts) and where to obtain required inputs. However, it does not explicitly contrast with sibling tools like get_transactions, so it loses a point for lacking explicit exclusions or alternative selection criteria.

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