process_due_reminders

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 explains that cancelled appointments' reminders are dropped, failed deliveries stay pending for the next run, and the limit controls batch size. This is meaningful behavioral context beyond the bare operation name.

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, front-loaded with the core purpose, and uses a clear structure with a short paragraph, Args section, and example. Every sentence contributes useful information without redundancy.

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 one optional parameter, an output schema, and moderate complexity. The description covers the core processing behavior, edge cases (cancelled/failed), and usage cadence. It omits return-value details, but the presence of an output schema reduces the need to describe them in prose.

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 schema only lists 'limit' as an integer with a default of 50, but the description defines it as 'Maximum to process in one pass.' This adds clear semantic meaning that the schema alone does not convey.

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 'Send every reminder that has come due' and then elaborates that it picks up all pending reminders with passed send times and active appointments. This clearly identifies the tool as a batch reminder-processing action, distinguishing it from the single-purpose sibling tool 'send_reminder'.

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 phrase 'Run this periodically' gives explicit guidance on when to use the tool, and the details about cancelled and failed reminders explain the operational context. However, it does not explicitly mention when to prefer send_reminder over this tool or list exclusions.

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