Generate an ElevenLabs agent system prompt

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

No annotations are provided, so the description must convey behavioral traits. However, it focuses solely on the output content and does not disclose side effects, authentication requirements, rate limits, or whether the tool performs API calls or local generation. This leaves significant gaps 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 a single well-structured sentence that efficiently communicates the tool's purpose and output components with no superfluous words.

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 has 7 parameters and an output schema, the description covers the key aspects of what the prompt includes. However, it lacks behavioral context, which is partially mitigated by the output schema. Overall, it provides sufficient context for selecting this tool over siblings.

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 meaning beyond the schema; it lists the optional parameters in a summary but provides no additional constraints, examples, or usage tips.

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 generates a production-grade system prompt for an ElevenLabs conversational agent acting as a business phone receptionist, listing specific components like identity, job, voice style, booking flow, guardrails, and escalation rules. This differentiates it from sibling tools such as write_phone_script or simulate_receptionist_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 implies usage when creating a system prompt for a phone receptionist AI, but does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention exclusionary conditions or prerequisites.

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