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

Annotations indicate this is a non-read, non-idempotent, non-destructive action. The description adds valuable behavioral context: it makes an outbound phone call, returns a callId immediately (asynchronous), and describes the possible outcomes including failure modes. This goes beyond the annotations by explaining the async nature and result 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 two sentences, front-loading the core action and outcome. Each sentence adds value: the first defines what the tool does, the second explains the result and immediate return. No wasted words; it's compact and informative.

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?

Given the tool's moderate complexity (9 params, 2 required, no output schema), the description covers key aspects: the action, immediate return, and result semantics (outcome types). It doesn't explain how parameters interact (e.g., slots vs timePreference) but that is minor since the schema is complete. It also mentions webhookUrl indirectly through result, so it's fairly complete.

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 is 100%, so all parameters are already documented in the schema. The description adds a bit of context by mentioning 'appointment (startISO, timezone, durationMinutes, attendee, subject)' which maps to some parameters, but it doesn't add meaningful semantics like delegation rules for 'slots' vs 'timePreference'. Thus baseline 3 is appropriate.

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 primary action ('Place an outbound AI phone call to set up a meeting') and specifies the resource (a phone call for appointment setting). It distinguishes itself from siblings by explicitly mentioning the outcome types and linking to get_call for polling, which is a distinct workflow from place_call and get_call.

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 context on when to use this tool (to set up a meeting via AI phone call) and mentions using get_call for results. However, it doesn't explicitly state when NOT to use it or contrast with siblings like place_call, which is a gap. But the clear purpose and start of the workflow give enough guidance for most cases.

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