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 mentions that the data is 'live from Meta' (indicating freshness) and lists the return fields (id, name, event type, creation time, rule). However, it does not disclose pagination behavior beyond what the schema describes, nor does it mention potential rate limits or error conditions. This is adequate but not rich.

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 concise—three sentences—and front-loads the primary action and resource. It efficiently conveys purpose, context, and use cases without repetition or filler. Every sentence adds value.

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 three parameters and no output schema or annotations, the description is fairly complete. It covers the purpose, the type of data, return fields, and common use cases. It omits explicit mention of pagination (though the 'after' parameter in schema hints at it) and rate limits, but these are not critical for basic invocation. Overall, it provides enough context for an agent to use the 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?

Schema description coverage is 100%, so the baseline is 3. The description does not add any parameter-specific details beyond what the schema already provides; it only references the action and return fields. It doesn't clarify parameter syntax or edge cases, so it earns the baseline score.

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 the action ('List an ad account's custom conversions'), the specific resource, and adds context on what custom conversions are ('CAPI/pixel conversion definitions used as optimization or attribution events') with an example. It also lists the returned fields, distinguishing it from sibling list tools by focusing on the exact entity type.

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 gives explicit use cases: 'Use to look up a custom conversion id before building a sales/leads ad set, or to audit which conversions exist.' This clearly indicates when to invoke the tool. It does not explicitly name alternative tools or state when not to use it, but the use cases are specific enough to guide an agent.

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