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speak

Reads a short message aloud to the user, delivering a spoken TL;DR of your answer. Supports interrupting current speech and using different speaker identities.

Instructions

Speak a short message aloud to the user through their speakers.

Use this to deliver a spoken TL;DR alongside (not instead of) your written answer: 1-3 conversational sentences summarizing the outcome, a finding, or a question. Never read code, file paths, or long explanations aloud.

You send only the text: voice, speed and language belong to the daemon (the user controls them on the dashboard). To deliberately switch your voice, call change_voice.

Concurrent speech is serialized: by default a new call WAITS for the current utterance to finish (queued), and for the user to finish speaking. Set interrupt=True to cut the current utterance off and speak immediately — use it only when your previous words are now stale (e.g. the user corrected you mid-answer).

Args: text: What to say. Plain conversational prose. Mark the key words the listener must catch with markdown bold (like this) — they get vocal emphasis and show bold on the live dashboard. Also supports inline speech tags like [pause] or [laugh] and wrapping tags like text. interrupt: Cut off any utterance currently playing and speak now. speaker: ONLY for subagents. If you are a subagent (Task/Agent tool), pass your role name here (e.g. "researcher") — the dashboard shows the message under that name with its own portrait, and the daemon gives you a stable voice distinct from the main agent's. The main agent must leave this empty.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
speakerNo
interruptNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations, the description carries full burden and does so thoroughly: it discloses serialized/concurrent speech queuing, interrupt semantics, that only text is sent (voice/language controlled by daemon), and speaker-role constraints for subagents. This is rich behavioral context beyond the schema.

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 long but well-structured: purpose first, then usage guidelines, then behavioral notes, then parameter details. Every section earns its place, though the opening sentence and the second sentence partially overlap in saying it's a short spoken message.

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

Completeness5/5

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

Given the tool's complexity (queueing, interrupt, subagent speaker, formatting tags), no annotations, and an output schema, the description covers all necessary context: when to use, exclusions, behavior, parameter semantics, and related tools. It is a complete standalone guide.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate and does. It explains text formatting (markdown bold, [pause], [laugh], <soft> tags), the exact meaning of interrupt, and the speaker parameter's subagent-only usage with dashboard implications.

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 immediately states 'Speak a short message aloud to the user through their speakers,' a specific verb+resource pairing. It further scopes usage to 'a spoken TL;DR alongside (not instead of) your written answer' and explicitly contrasts with change_voice, distinguishing it 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 Guidelines5/5

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

Provides explicit when-to-use guidance: deliver 1-3 conversational sentences summarizing outcome/finding/question, never read code/paths/long explanations. It also names the alternative change_voice for switching voices and explains interrupt behavior, giving clear conditions for interrupt=True.

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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