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Speak text aloud

hs_speak

Speak text aloud on Mac via speech synthesis. Returns immediately, interrupting any ongoing speech for instant audio feedback.

Instructions

Say something out loud through the Mac speech synthesiser. Returns as soon as speech starts rather than waiting for it to finish. Calling again interrupts whatever is currently being spoken.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rateNoWords per minute. The default is around 175.
textYesWhat to say.
voiceNoVoice name from hs_list_voices. Omit for the system default.
Behavior4/5

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

With no annotations, the description must disclose behavior on its own. It does so by noting the non-blocking return ('Returns as soon as speech starts') and the interrupt behavior on repeated calls. This goes beyond merely stating 'speak text' and gives the agent actionable behavioral context. It could mention resource requirements (e.g., audio output) but the purpose makes that obvious.

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

Conciseness5/5

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

The description is two sentences, front-loaded with the core purpose and followed by two critical behavioral traits. No redundant or filler words; every clause earns its place. It is both concise and informative.

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 tool's simplicity (3 params, all documented, no output schema, no annotations), the description covers the essential aspects: purpose, return timing, and interrupt behavior. It misses minor context like potential error states or prerequisites, but these are not critical for such a straightforward tool. It is adequate for correct selection and invocation.

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

Parameters3/5

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

Schema coverage is 100%, with each parameter (text, rate, voice) having descriptive comments. The tool description itself adds no parameter-level detail beyond the schema, so the baseline of 3 applies. It doesn't enhance or contradict the schema, but also doesn't need to given the high schema coverage.

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 clearly states the tool's purpose: 'Say something out loud through the Mac speech synthesiser.' It uses a specific verb ('say') and resource ('Mac speech synthesiser'), and the behavioral note about returning early and interrupting distinguishes it from hypothetical alternatives. It is unambiguous and distinct from sibling tools.

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 when to use it (to speak text aloud) and includes an explicit usage note: 'Calling again interrupts whatever is currently being spoken.' It doesn't discuss alternatives or exclusion cases, but given the tool's unique function (speech output) among siblings, sufficient guidance is provided.

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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