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by com.thefilmradar
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Speak in Cloned Voice

lab_voice_tts

Speak text in a project's cloned voice (via lab_voice_clone) — SYNCHRONOUS, returns a ready audio_url, no job_id. The voice house is whichever one cloned this voice; you do not pick it here. Consent-sensitive like the clone itself: only speak text you have the right to put in that voice's mouth.

Input Schema

NameRequiredDescriptionDefault
textYesThe line(s) to speak in this voice.
get_costNoPrice this call instead of running it: returns the estimate and the balance, charges nothing, produces no audio. Worth doing before a long passage, because both houses bill by the size of the text, not per run — so the same tool can cost wildly different amounts depending on what you hand it. The rates behind the estimate are not repeated here; lab_list_models carries them.
providerNoCross-check, not a choice: the house that cloned this voice is the one that speaks with it, because a voice id from one house means nothing to the other. Pass it only to assert what you believe the voice is; a mismatch is refused before anything is charged. Omit it and the stored voice decides. Which house a voice belongs to: lab_list_voices. What each house can do: lab_list_models.
voice_idYesA cloned voice's id (lab_cloned_voices.id, from lab_voice_clone or lab_list_voices) — positive integer as string, NOT the raw provider voice id.
project_idYesProject id (from lab_list_projects) — positive integer as string
nur_eigene_datenNoOnly for a model that sends inputs to China or a US recipient without a documented basis, when the step carries images, clips, voices or faces. Means: this material shows or contains no real person other than the human using this account. Set it ONLY after the human has said exactly that for THIS step; never assume it, never reuse it for the next step. Not needed when the human has declared this material in the FilmLab app: the backend reads that declaration, also for material derived from it; only the app can store one. An LK reference, a licensed likeness or another person's agreement does not replace it. Without it the backend refuses with drittland_dritte_gesperrt before any charge; then use a non-gated model or text only.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / nur_eigene_daten / description
      Previous value: -"Only for a model that sends inputs to China or a US recipient without a documented basis, when the step carries images, clips, voices or faces. Means: this material shows or contains no real person other than the human using this account. Set it ONLY after the human has said exactly that for THIS step; never assume it, never reuse it for the next step. An LK reference, a licensed likeness or another person's agreement does not replace it. Without it the backend refuses with drittland_dritte_gesperrt before any charge; then use a non-gated model or text only."New value: +"Only for a model that sends inputs to China or a US recipient without a documented basis, when the step carries images, clips, voices or faces. Means: this material shows or contains no real person other than the human using this account. Set it ONLY after the human has said exactly that for THIS step; never assume it, never reuse it for the next step. Not needed when the human has declared this material in the FilmLab app: the backend reads that declaration, also for material derived from it; only the app can store one. An LK reference, a licensed likeness or another person's agreement does not replace it. Without it the backend refuses with drittland_dritte_gesperrt before any charge; then use a non-gated model or text only."
  2. Changed1 schema field changed
    • addedInput schema / properties / nur_eigene_daten
      Added value: +{
+  "description": "Only for a model that sends inputs to China or a US recipient without a documented basis, when the step carries images, clips, voices or faces. Means: this material shows or contains no real person other than the human using this account. Set it ONLY after the human has said exactly that for THIS step; never assume it, never reuse it for the next step. An LK reference, a licensed likeness or another person's agreement does not replace it. Without it the backend refuses with drittland_dritte_gesperrt before any charge; then use a non-gated model or text only.",
+  "type": "boolean"
+}
  3. Changed1 schema field changed
    • addedInput schema / additionalProperties
      Added value: +false
  4. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations only declare non-readOnly and non-destructive, so the description carries real weight: it discloses the synchronous execution model and that the result is a ready audio_url with no job_id to poll. The consent warning adds a behavioral constraint the annotations never express; only the absence of any mention of failure modes or cost/auth beyond consent keeps it from a 5.

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?

Three tight sentences, front-loaded with the execution model, then the provider constraint, then the consent caveat. No filler, though the parenthetical '(via lab_voice_clone)' and the semi-idiomatic phrasing lean terse enough to be slightly cryptic.

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 generation tool with no output schema, the description does the one thing it must: tells the agent the call is synchronous and returns audio_url rather than job_id. With all six parameters documented in the schema and safety covered by annotations, the definition is sufficient to invoke 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 description coverage is 100%, so the parameters (including the provider cross-check and the get_cost flag) are already fully explained in structured data. The description only reinforces that the caller does not choose the voice house here, which the provider schema property already states — baseline 3.

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 concrete verb and resource (speak text in a project's cloned voice) and immediately differentiates itself from the clone step by pointing at lab_voice_clone as the prerequisite. A reader can separate it from lab_dub_tts or lab_voice_clone without opening any schema.

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 clear operating context — synchronous, returns audio directly, voice house is fixed by the clone — plus a consent condition that gates use. It does not name a competing tool (e.g. lab_dub_tts) as an alternative or state when-not-to-use, so it stops short of a 5.

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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