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

With no annotations provided, the description carries the full burden. It discloses the pipeline stages, language detection capability, and the fact that it's the same pipeline as the demo (but without the 'full AI brain'). It also notes it's free and text-only, which are key behavioral traits for an AI agent.

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 extremely concise: two sentences that effectively front-load the purpose and then provide usage instructions. Every sentence adds value with no redundancy or 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?

Despite moderate complexity, the description covers input, behavior, constraints, and hints at output. Since an output schema exists, the lack of explicit return value details is acceptable. The description is complete for an AI agent to understand and invoke 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 coverage is 100%, so the baseline is 3. The description adds value by providing an example (Spanish language switch) and explaining that callerSays is the caller's lines in order. This helps the agent understand how to format input beyond the schema's description.

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 tool's purpose: role-playing a phone call with Lobby's receptionist call engine. It lists key features (greeting, booking, lead capture, language detection) and explicitly distinguishes from sibling tools like calculate_missed_call_cost, making its purpose unmistakable.

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 clear usage guidance: the user plays the caller, passes each line, and receives transcript and outcome. It specifies constraints (free, text-only, max 6 lines) and hints at language switching. While it doesn't explicitly contrast with siblings, the context makes it obvious when to use this tool.

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