generate_voiceoverConvert text into MP3 voice-over audio and a word-timed SRT subtitle file for narrated short videos with matching captions.
Free neural text-to-speech (Microsoft Edge voices, 300+ voices, 70+ languages) to MP3, plus an SRT subtitle file timed to the words.
| Name | Required | Description | Default |
|---|---|---|---|
| rate | No | ||
| text | Yes | ||
| pitch | No | ||
| voice | No | ||
| language | No | ||
| output_dir | No |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already flag readOnlyHint=false and openWorldHint=true, so the agent knows this writes artifacts and reaches a network service. The description adds the engine ('Microsoft Edge voices') and the second output artifact (SRT subtitles), which is real added context, but it says nothing about where files land, what is returned (paths?), latency, or failure modes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single dense sentence, front-loaded with the core capability and output formats. The parenthetical voice/language counts earn their place; nothing is wasteful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a six-parameter generative tool with zero schema descriptions and no output schema, the definition is too thin: an agent cannot tell how to format rate/pitch, whether voice must come from list_voices, or what the return value will be. The 'free' and engine details are nice but not sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% across six parameters, so the description must carry the burden and largely does not. It loosely implies 'voice' and 'language' semantics via '300+ voices, 70+ languages' but never explains rate/pitch formats (e.g. '+10%', '-2Hz'), the role of output_dir, or how voice and language interact.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Names a specific verb+resource (neural text-to-speech generation) and even names the concrete artifacts produced: an MP3 and an SRT subtitle file timed to the words. It is clearly distinct from list_voices or make_short_video, though it does not explicitly state that distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this versus siblings: it never says to call list_voices first to discover valid voice names, nor what to do when text exceeds the 6000-character limit. Usage is only implied by the tool's obviousness.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.