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by io.clueso
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Set voice

set_voice

Set the voiceover voice for every clip in a project, or only for the clips in clip_ids.

Use this to apply a clueprint's voice (read voiceover.voice.name and voiceover.voice.engine from the clueprint source data), or to switch all clips to a specific voice in one call. When the user names specific clips, pass their ids in clip_ids so the other clips keep their voice. The voice is looked up by name (case-insensitive; a saved voice's code also works), preferring voice_engine.

Never guess a name: a name that matches nothing applies the workspace default and returns matched: false with a note. Then pick a real voice with find(type='voices'), re-apply, and tell the user. engine_substituted: true means the named voice exists only on another engine and was applied there.

Common engines: 'eleven' (ElevenLabs), 'cartesia', 'google'.

ElevenLabs voices use the latest voice generation unless voice_version says otherwise; a voice the workspace saved keeps its saved version. Leave it unset; pass "legacy" ONLY when the user explicitly asks for the legacy/older voice generation.

Input Schema

NameRequiredDescriptionDefault
clip_idsNoClip ids to change the voice on. Omit to change EVERY clip in the project.
project_idYesThe project (guide) ID
voice_nameYesVoice name exactly as find(type='voices') lists it (e.g. 'Alex').
voice_engineYesVoice engine — 'eleven', 'cartesia', 'google', etc.
voice_versionNoElevenLabs voice generation. Leave unset: latest, except a voice the workspace saved keeps its saved version. Use 'legacy' ONLY when the user explicitly asks for the legacy/older voice generation; never choose it yourself. Ignored for non-ElevenLabs voices.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / voice_version / description
      Previous value: -"ElevenLabs voice generation. Leave unset (latest). Use 'legacy' ONLY when the user explicitly asks for the legacy/older voice generation; never choose it yourself. Ignored for non-ElevenLabs voices."New value: +"ElevenLabs voice generation. Leave unset: latest, except a voice the workspace saved keeps its saved version. Use 'legacy' ONLY when the user explicitly asks for the legacy/older voice generation; never choose it yourself. Ignored for non-ElevenLabs voices."
  2. Changed1 schema field changed
    • changedInput schema / properties / voice_name / description
      Previous value: -"Voice name as stored in the voices table (e.g. 'Alex', 'Sofia')"New value: +"Voice name exactly as find(type='voices') lists it (e.g. 'Alex')."
  3. Changed2 schema fields changed
    • addedInput schema / properties / clip_ids
      Added value: +{
+  "description": "Clip ids to change the voice on. Omit to change EVERY clip in the project.",
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}
    • addedInput schema / properties / voice_version
      Added value: +{
+  "description": "ElevenLabs voice generation. Leave unset (latest). Use 'legacy' ONLY when the user explicitly asks for the legacy/older voice generation; never choose it yourself. Ignored for non-ElevenLabs voices.",
+  "enum": [
+    "latest",
+    "legacy"
+  ],
+  "type": "string"
+}
  4. Changed4 schema fields changed
    • removedInput schema / properties / context
      Removed value: -{
-  "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
-  "type": "string"
-}
    • removedInput schema / properties / conversation_id
      Removed value: -{
-  "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.",
-  "type": "string"
-}
    • removedInput schema / properties / llm_model
      Removed value: -{
-  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
-  "type": "string"
-}
    • changedInput schema / required
      Previous value: -[
-  "project_id",
-  "voice_name",
-  "voice_engine",
-  "context",
-  "llm_model"
-]New value: +[
+  "project_id",
+  "voice_name",
+  "voice_engine"
+]
  5. Changed4 schema fields changed
    • addedInput schema / properties / context
      Added value: +{
+  "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
+  "type": "string"
+}
    • addedInput schema / properties / conversation_id
      Added value: +{
+  "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.",
+  "type": "string"
+}
    • addedInput schema / properties / llm_model
      Added value: +{
+  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
+  "type": "string"
+}
    • changedInput schema / required
      Previous value: -[
-  "project_id",
-  "voice_name",
-  "voice_engine"
-]New value: +[
+  "project_id",
+  "voice_name",
+  "voice_engine",
+  "context",
+  "llm_model"
+]
  6. Changed2 schema fields changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • removedInput schema / additionalProperties
      Removed value: -false
  7. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Goes well beyond the annotations (which only say non-readOnly, non-destructive) by disclosing failure semantics: an unmatched name silently applies the workspace default and returns `matched: false`, and `engine_substituted: true` means the voice was applied on a different engine. It also explains name lookup (case-insensitive, saved code accepted) and the safe default for `voice_version`.

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?

Front-loaded with scope, then usage, then failure modes, then the version caveat — a logical order with no filler sentences. It runs a bit long, and the 'Common engines' line partly restates the enum-ish schema examples, but each paragraph still carries actionable behavior.

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?

There is no output schema, and the description compensates by naming the fields an agent must inspect (`matched`, `engine_substituted`, `voiceover.voice.name`/`engine`). Combined with the mutation scope and the recovery procedure, an agent has everything needed to call and interpret this correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3, but the description adds real meaning: lookup is case-insensitive by name, a saved voice's code also works, `voice_engine` is a preference hint rather than a hard constraint, and omitting `clip_ids` means every clip. It also adds the 'leave unset / legacy only on explicit request' rule for `voice_version`.

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?

Opens with a specific verb+resource and immediately states the two scopes (every clip in a project, or only those in `clip_ids`). This distinguishes it from siblings like `update_audio`, `voiceover_batch`, or `update_clips`, which do not target voice assignment.

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?

Explicitly says when to use it (apply a clueprint's voice, or switch all clips in one call) and gives the conditional rule for `clip_ids` when the user names specific clips. It also routes the agent to `find(type='voices')` as the recovery path and warns against guessing a name.

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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