meta_ads_audiences_get

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

Declares 'Read-only' indicating no mutation, and lists returned fields. Annotations absent, so description carries full burden. Adequate for a simple fetch.

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?

Three sentences, front-loaded with purpose, efficient field listing, no fluff.

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?

No output schema, but description enumerates returned fields. Includes read-only note and usage guidance. Sufficient for a get 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?

Schema coverage 100% so baseline 3. Description notes audience_id as 'returned by meta_ads_audiences_list', adding helpful context beyond 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?

Description clearly states 'Fetches the full detail record for a single Custom Audience' with specific fields returned. Differentiates from siblings like list and delete.

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?

Explicitly mentions use before meta_ads_audiences_delete or create_lookalike, providing clear context for when to invoke. Does not explicitly state when not to use, but context is sufficient.

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