merit_list_gl_batches

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses the endpoint and date/dateType constraints, but it does not mention authentication requirements, output format, pagination, or any side effects. Listing does imply a read operation, but the description adds limited behavioral context beyond the endpoint.

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 compact and front-loaded with the core purpose and endpoint, followed by only the essential constraints and dateType semantics. No filler or redundant material.

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?

For a list operation with three parameters and no output schema, the description covers the required inputs and their constraints. It lacks guidance on results format and sibling-tool selection, but the core calling contract is present.

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?

Schema description coverage is 100%, so even without parameter detail in the description the baseline is 3. The description restates the ISO date format, the 3-month maximum interval, and the dateType meaning, adding little beyond the schema descriptions.

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 clearly identifies the operation as listing Merit Aktiva general-ledger batches and includes the explicit API endpoint. However, it does not explicitly distinguish this from sibling tools such as merit_list_gl_batches_full or merit_get_gl_batch, so it falls short of full sibling differentiation.

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?

No guidance is given about when to choose this tool over alternatives such as merit_list_gl_batches_full or merit_get_gl_batch. The parameter constraints are stated, but there is no context for selection decisions.

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