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by com.voicehue
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Create a long speech job

create_speech_job

Queue a long text (up to 20,000 characters) for speech. Returns a job id at once; call get_speech_job with it until the status is completed, then download the audio from its link. Use text_to_speech instead for texts up to 3,000 characters. The text is charged once, only when all of it was spoken.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "text": "<text>",
      "voice": "<voice>"
    },
    "name": "create_speech_job"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYesThe text to speak.
speedNoSpeaking speed, 0.5 to 2.
voiceYesA voice id from list_voices.
formatNoAudio format. MP3 is the default.mp3
callback_urlNoOptional https URL that receives the finished job as a signed POST.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior4/5

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

Beyond the annotations (readOnlyHint=false, openWorldHint=true, idempotentHint=false, destructiveHint=false), the description discloses the async contract (returns immediately), the polling loop, and a billing rule ("charged once, only when all of it was spoken"). It does not cover job lifetime/expiry or what happens on failed or partial jobs, which are the remaining behavioral unknowns for a queue-and-poll tool.

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, front-loaded with the action and limit, then the async follow-up, then the sibling alternative and billing note. No restatement of the title and nothing that could be cut.

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?

For a 5-parameter async tool with no output schema, the description supplies the return value (job id), the retrieval path (get_speech_job status then audio link), and the cost model — everything needed to call it and complete the workflow correctly.

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 text, voice, speed, format and callback_url are already fully documented with ranges and defaults. The description reinforces the text length ceiling and the voice sourcing but adds no new meaning for speed, format or callback_url; baseline 3 applies when the schema carries the load.

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 names a specific verb and resource ("Queue a long text ... for speech") and pins down the scope with a character limit (20,000). It also distinguishes itself from the short-text sibling by name, so an agent can tell the two apart without opening either schema.

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?

Explicit routing rule: "Use text_to_speech instead for texts up to 3,000 characters." It also supplies the follow-up procedure — poll get_speech_job with the returned id until completed, then download the audio — which is exactly the when/how guidance an agent needs for an async tool.

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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