export_subscribers

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

With no annotations provided, the description fully owns behavioral disclosure. It details the asynchronous generation and waiting process, the absence of paging, and the special handling of unexportable columns via `missing_columns` rather than failure. This goes beyond typical descriptions by explaining edge cases and operational behavior, giving the agent critical context for invocation and error handling.

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 dense but every sentence contributes meaningful information. It front-loads the primary purpose, then adds differentiators and operational details. The enumeration of engagement metrics is long but serves to differentiate from list_subscribers. It is not overly verbose for the complexity it covers.

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 tool with no output schema, the description provides essential context about return behavior: it waits asynchronously, returns parsed records, and reports missing columns. It also clarifies the full matching set and the relationship to list_subscribers. While it doesn't detail error handling or the exact record structure, the provided information is sufficient for most invocation decisions.

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 already provides 100% coverage with detailed descriptions for each parameter, including the full column enum with human-readable labels. The description adds value by clarifying that filters are the same as list_subscribers, the export covers the whole matching set with no paging, and the async wait behavior explains the max_wait_seconds parameter. This enhances the parameter semantics beyond the schema alone.

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 a specific action ('Export subscribers') with the full column values and distinguishes itself from the sibling list_subscribers by highlighting that it returns engagement metrics list_subscribers cannot return. The phrase 'covers the whole matching set — there is no paging' further clarifies its scope, making it unambiguous what this tool does.

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 strong usage context by explicitly referencing list_subscribers ('Takes the same filters as list_subscribers') and contrasting the return capabilities ('engagement metrics list_subscribers can filter on but not return'). This implies when to use this tool over the alternative, though it does not explicitly state exclusions or when to prefer list_subscribers. The lack of paging and asynchronous behavior also guide usage expectations.

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