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timps_voice_agent_designer

Design production voice agents by defining persona, system prompts, SSML, tool calls, barge-in handling, escalation rules, latency budgets, and test utterances.

Instructions

Design a production voice / phone agent: persona, system prompt, SSML, tool calls, barge-in handling, escalation rules, latency budget, and test utterances.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestNoPlain-English task or context for the agent.
languageNoPrimary programming language (default: python).python
Behavior4/5

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

No annotations are provided, so the description carries the burden, and it does well by enumerating the concrete outputs (persona, SSML, escalation rules) and constraints (latency budget, barge-in). It misses a few behavioral specifics like idempotency or whether it modifies state, but it's still quite transparent for a design/generation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, dense, front-loaded sentence with a valuable colon-separated list of features. Highly efficient, though it abstracts a great deal of detail that might merit a `sibling` callout.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the zero required parameters and no output schema, the description covers the design scope exceptionally well. It could be more complete with a note on expected output format, but it's quite thorough for the tool's purpose.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% — both 'request' and 'language' are documented. The description's rich enumeration of deliverables adds significant context the schema lacks, showing how it complements the structured parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Design') and enumerates a comprehensive list of voice-agent artifacts (persona, system prompt, SSML, tool calls, etc.), clearly distinguishing it from sibling tools like timps_routing_agent or generic design agents. The scope is unmistakable and actionable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies a design-time, blueprints-style use case (as opposed to other agent tools like simulators or debuggers), covering context and deliverables. However, it does not explicitly state when NOT to use it or name an alternative for different needs, so it loses a point.

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

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