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generate_dialogue

Generate multi-speaker dialogue for character conversations. Assign voices to dialogue lines and produce audio output.

Instructions

Generate multi-speaker dialogue using ElevenLabs Text-to-Dialogue V3 via kie.ai. Great for conversations between characters. Downloads to kie/assets/raw/.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
waitNoSet false to submit and return immediately with the task_id (async mode) — then poll with check_task and fetch with download_result. Recommended for long generations to avoid client-side watchdog timeouts.
dialogueYesArray of dialogue lines with voice assignments
filenameNoOutput filename. Auto-generated if omitted.
stabilityNoVoice stability — kie accepts exactly 0 (creative), 0.5 (natural), or 1 (robust)
download_dirNoAbsolute directory to save the file(s) into (created if missing). Defaults to the server's kie/assets/raw/. Must be absolute — the MCP server's working directory is not the caller's.
language_codeNoLanguage code (e.g. "en")
max_wait_secondsNoOverride the blocking-mode polling budget in seconds (defaults: image 600, video 900, audio 300, speech 300). Ignored when wait=false.
Behavior3/5

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

No annotations are provided, so the description carries full burden. It mentions the download destination and the service used, but lacks details on side effects, cost, rate limits, or error behavior. The schema provides async mode details, but the description itself is minimal.

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?

The description is two concise sentences, front-loaded with the action verb and resource. Every word adds value with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 7 parameters and uses a complex async workflow, but the description is minimal. The schema compensates with thorough parameter documentation, yet the description does not cover return values or error handling. Adequate but not comprehensive.

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 all parameters well. The description adds no extra meaning beyond noting the download directory, so a baseline of 3 is appropriate.

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 clearly states the tool generates multi-speaker dialogue, mentions the underlying service (ElevenLabs Text-to-Dialogue V3 via kie.ai), and indicates the output location. This distinguishes it from sibling tools like generate_tts (single speaker) and generate_music (audio generation).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description says 'Great for conversations between characters,' implying a use case, but it does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention prerequisites or constraints.

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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