List QuickBooks Invoices

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

Annotations already cover key behavioral traits (read-only, open-world, idempotent, non-destructive), but the description adds valuable context beyond this: it specifies the return format options ('markdown' or 'json'), lists the fields in the response, and mentions pagination behavior via limit/offset. This enhances transparency without contradicting the annotations.

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 well-structured and front-loaded with the core purpose, followed by organized sections for Args and Returns. Every sentence adds value: the first sets context, and the bullet points efficiently detail parameters and outputs without redundancy. It's appropriately sized for a tool with 7 parameters.

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?

Given the tool's complexity (7 parameters, no output schema), the description is complete: it covers the purpose, all parameters with semantics, return format options, and response fields. With annotations providing safety and behavioral hints, and the description filling in usage and output details, there are no significant gaps for an AI agent to invoke the tool correctly.

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?

With 100% schema description coverage, the baseline is 3, but the description adds meaningful semantic context: it groups parameters (e.g., 'limit/offset: Pagination'), clarifies status enum values with descriptions like 'open', 'paid', or 'overdue', and explains the purpose of response_format. This goes beyond the schema's technical definitions, improving understanding.

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 states the specific action ('List invoices from QuickBooks Online') and resource ('invoices'), distinguishing it from sibling tools like qbo_create_invoice (which creates rather than lists) and qbo_list_customers/vendors (which list different resources). The verb 'List' is precise and unambiguous.

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 description provides clear context for usage through the 'with filtering options' phrase and the detailed parameter explanations, which help understand when to apply specific filters. However, it doesn't explicitly state when to use this tool versus alternatives like qbo_list_customers or qbo_profit_loss_report, nor does it mention any prerequisites or exclusions.

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