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Pedra MCP Server

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Generate voiceover audio

pedra_generate_voice

Convert text script into voiceover audio and return an audioId used to attach narration and synced subtitles to your video.

Instructions

Render a voiceover from a script via text-to-speech. Returns an audioId — pass it to pedra_create_video / pedra_update_video as voice.audioId to attach the narration (with synced subtitles).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe script to narrate (max 1000 characters).
languageNoVoice language, e.g. "English", "Español". Defaults to English.
Behavior4/5

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

Annotations already indicate a non-read-only, non-destructive action ('readOnlyHint': false, 'destructiveHint': false). The description adds valuable context: returns an audioId, attaches narration with synced subtitles. It does not detail potential side effects like cost or limits, but the added usage info compensates.

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?

Two sentences, no wasted words. First sentence declares the action and return; second explains integration. Front-loaded with critical information.

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?

The tool has only two parameters and no output schema. The description explains the return value and its usage, covering the essential context. It does not mention error handling or limitations beyond the schema's max characters, but it is complete for its simplicity.

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%, so the description is not required to explain parameters. It adds no extra meaning beyond what the schema already provides (e.g., text max length, language default). Baseline score of 3 is appropriate.

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 ('render') and resource ('voiceover from script'), clearly distinguishing it from the sibling 'pedra_generate_voice_script'. It states the return value (audioId) and how to use it, leaving no ambiguity.

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 explicitly explains when to use the tool (render voiceover from script) and what to do with the output (pass to video tools as voice.audioId with synced subtitles). It does not explicitly say when not to use it or list alternatives, but the context is clear enough for an AI agent.

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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