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

Besides the sparse annotations, the description discloses that this is a write/insert operation, includes validation and deduplication behavior, runs sync_fast, and directs the agent to get_outcome for results. It also surfaces cost and latency, which are useful operational traits not present in the annotations.

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 organized into compact labeled sections (purpose, example, when to use, when not to use, cost, latency, execution) with no filler. Every line earns its place and the core purpose is front-loaded.

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 nested prospect object, no output schema, and async execution, the description covers the critical operational facts: when to call, when not to call, what the call looks like, cost, latency, and where to retrieve the result (get_outcome). Remaining parameter details are available in the input schema, so nothing essential is missing.

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?

There is no prose parameter list, but the concrete example maps smb_id, prospect (name, phone, email), and source to a realistic call, which compensates for the 50% schema coverage. idempotency_key and consent_record_id are left to the schema's own descriptions, so the description does not fully carry parameter semantics by itself.

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 names a concrete operation — structured intake of a prospect into an SMB's funnel/CRM/direct-booking pipeline — and distinguishes it from confirmed bookings via the WHEN NOT TO USE clause. The example user query reinforces the exact use case and tool 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?

Explicit WHEN TO USE and WHEN NOT TO USE sections clearly define the triggering condition (prospect expresses interest) and rule out confirmed bookings (pointing to schedule_appointment) and bulk imports. No inference is needed.

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