meta_get_ad_studies

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'List' implies a read-only operation, and the description usefully states the output includes study type, status, and cells. However, it does not disclose pagination behavior, result limits, or any account-level requirements, which would strengthen transparency.

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 a single concise sentence that front-loads the primary action and resource, then adds the key output details. Every word contributes meaning, with no redundant phrasing or filler.

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 one-parameter list tool with no output schema, the description is largely complete: it states the resource, scope, and meaningful output fields. It lacks explicit mention of pagination or relationship to study results, but these are not critical for a straightforward listing tool.

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 only parameter, adAccountId, is fully described in the schema with an example format ('act_123456789'). Since schema description coverage is 100%, the description does not need to add further parameter detail, and it does not attempt to repeat the schema.

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 uses a specific verb ('List') and identifies the exact resource ('conversion lift studies and A/B tests (Ad Studies)') scoped to an ad account. It also specifies the included fields (study type, status, cells), which clearly distinguishes it from sibling tools like meta_get_study_results that would retrieve study outcomes rather than the study list itself.

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 no guidance on when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. It simply states what the tool does, leaving the agent to infer appropriate usage from the tool name and sibling list alone.

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