get_reach_estimate

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

With no annotations provided, the description carries the full behavioral burden. It discloses that the tool returns a dictionary with users_lower_bound and users_upper_bound, that optimization_goal affects the estimate, and that currency defaults to the account currency. The word 'estimate' and the 'before creating' framing imply a non-mutating calculation. It could add more about limits or error behavior, but the key behavioral traits are present.

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 with a front-loaded purpose sentence followed by compact Args and Returns sections. Every element earns its place, and the parameter examples make the description easy to scan without being bloated.

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 four-parameter estimation tool, the description covers the core invocation details, parameter semantics, and return shape. The existence of an output schema reduces the need to describe return values further. It does not discuss authentication, rate limits, or edge cases, but those are not critical for understanding how to call this 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?

The input schema has 0% description coverage, but the Args section fully compensates: it gives a concrete example for act_id, a full targeting_spec dictionary example, valid optimization_goal values, and currency examples with default behavior. This adds substantial meaning beyond the schema's bare type definitions.

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 states a clear verb and resource: 'Estimate the potential audience reach for a given targeting spec before creating an ad set.' It clearly conveys what the tool computes and when it is meant to be used. It does not explicitly contrast itself with the similar sibling get_delivery_estimate, so it narrowly misses full 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?

The phrase 'before creating an ad set' provides clear usage context, and the Args examples show how to construct valid inputs. However, it gives no explicit guidance about when not to use this tool or which sibling alternative (e.g., get_delivery_estimate) might be more appropriate for a different estimate.

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