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Glama

falar

Converts short text into spoken audio through the PC speaker using a local Brazilian Portuguese voice, so users can hear responses read aloud.

Instructions

Fala o texto em voz alta no alto-falante do PC (voz brasileira local, Piper).

Use quando o usuário pedir para ouvir a resposta. Texto curto: markdown e código são tirados, e mais de ~1200 caracteres é cortado.

Input Schema

NameRequiredDescriptionDefault
textoYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses that the voice is local (Piper), Brazilian Portuguese, that markdown and code are stripped before speaking, and that input over ~1200 characters is cut. What it omits is operational behavior — whether the call blocks until speech finishes, what happens if there is no audio device, and what the output schema returns.

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?

Three short sentences: what it does, when to use it, and the input constraints — front-loaded with the action and with no filler or repetition of schema fields.

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?

For a one-parameter, non-destructive audio tool with an output schema already covering the return value, this is nearly complete. The only meaningful gap is the lack of any note on call behavior (blocking vs. fire-and-forget) or failure mode when audio is unavailable.

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 coverage is 0%, so the description must compensate, and it does: the single parameter 'texto' is explained as being spoken aloud, with preprocessing (markdown/code removed) and a ~1200-character truncation limit. It still says nothing about how the truncation is signalled or whether the caller should pre-shorten the text.

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?

States a specific verb and resource ('fala o texto em voz alta no alto-falante do PC') plus the engine and voice ('voz brasileira local, Piper'), which is enough for an agent to know exactly what the tool does and that it is not a file/audio-generation tool. No sibling overlaps with text-to-speech, so the absence of explicit sibling differentiation is not a gap.

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?

Gives an explicit trigger condition: 'Use quando o usuário pedir para ouvir a resposta.' It does not name a when-not case or an alternative, but no plausible alternative exists in the sibling list, so the guidance is effectively complete.

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