framesail

List voices

list_voices

Read-onlyIdempotent

List available TTS voices (id, label, preview audio URL) for a provider: "minimax" (default engine) or "elevenlabs". Match the project's voice_tts_provider (see get_project) so picked ids work with its engine. Returns {groups: {name: count}, voices}; the ElevenLabs catalogue is 150+ voices, so pass group (names from groups) rather than reading it all at once.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`group`	No	Return only this catalogue group (case-insensitive; e.g. "Narration", "Characters"). Empty returns every group — the ElevenLabs catalogue is 150+ voices, so filter it by group; the response's `groups` lists the valid names with counts.
`provider`	No	TTS engine to list voices for: "minimax" (default engine) or "elevenlabs"; match the project's voice_tts_provider	minimax

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds useful behavior beyond annotations: it reveals the response shape ({groups, voices}) and warns about the large ElevenLabs catalogue, guiding the agent to filter.

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 dense sentences with no filler: purpose, provider guidance, and response/filtering note are each front-loaded and necessary. The structure makes the key operational detail (large catalogue, use groups) easy to find.

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 low-complexity read-only tool with richly annotated schema and no output schema, the description supplies the essential missing pieces: return shape, provider-project matching, and group filtering. Nothing critical is left unexplained.

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 schema already documents both 'group' and 'provider' well. The description reinforces the provider choices and the group-filtering strategy but does not add substantial new parameter-level meaning beyond what the schema provides.

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 starts with a specific verb and resource: 'List available TTS voices' and names the returned fields (id, label, preview audio URL). It also distinguishes the two provider engines, making the tool's scope clear relative to sibling tools like list_voice_blocks.

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?

It gives clear practical context: match the project's voice_tts_provider (pointing to get_project) and filter by group for ElevenLabs to avoid reading 150+ voices. It does not explicitly name exclusions or alternatives, but the guidance is sufficient for correct use.

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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TDQS

A3.6/5.0

Disambiguation3/5

Several tool families overlap in purpose, such as await_jobs/get_workflow_status/get_pipeline_progress, update_segment_content/update_segment_prompts, director_note/project_director_note, and scan_script/rescan_voice_blocks. The descriptions do a good job distinguishing them, but an agent must read carefully to avoid misselection, and there are more than a couple of confusable pairs.

Naming Consistency4/5

The set overwhelmingly follows a verb_noun snake_case convention with clear prefixes like get_, list_, set_, update_, create_, and delete_. Minor exceptions such as director_note, project_director_note, browse_audio_library, and whoami keep it from being perfectly consistent.

Tool Count1/5

At 72 tools, this is far beyond the 50+ extreme range and creates a heavy navigation burden for an agent. Even though the pipeline is complex, this many tools is not well-scoped for an MCP surface.

Completeness4/5

The surface covers the full script-to-export pipeline: styles, assets, voices, storyboards, segments, scenes, and rendering all have substantial lifecycle support. Some gaps exist—no delete_channel, delete_segment, delete_voice_block, or delete_provider_key—but most missing operations can be worked around through existing tools.

Resources

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