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voice_lines

Voice every line of an episode's script with ElevenLabs (cached by hash: unchanged lines cost nothing) and generate its sound effects. Returns each line's length and the episode's approximate length.

Instructions

Voice every line of an episode's script with ElevenLabs (cached by hash: unchanged lines cost nothing) and generate its sound effects. Returns each line's length and the episode's approximate length.

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": {
      "slug": "<slug>"
    },
    "name": "voice_lines"
  }
}

Input Schema

NameRequiredDescriptionDefault
slugYesepisode slug, e.g. the-cursed-tape (or an example slug for read-only tools)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It does usefully disclose hash-based caching ('unchanged lines cost nothing') and that it returns line lengths plus an approximate episode length, but it omits whether this is a synchronous or async job (siblings like job_status/list_jobs hint at job-based work), what happens to previously generated audio, and any cost/rate implications beyond caching.

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?

A single tightly written sentence that front-loads the core action and packs the caching caveat and return info without waste. Every clause earns its place.

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?

There is no output schema and no annotations, and the description partially compensates by naming what it returns. However, for a potentially costly, long-running synthesis-and-SFX operation, it leaves out whether the call blocks or spawns a job, what happens on partial failure, and prerequisites, which is a meaningful gap.

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?

There is a single parameter ('slug') with 100% schema description coverage, so the schema already defines it. The description adds no meaning about the slug beyond the example format already in the schema, so the 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?

States a specific verb and resource: voice every line of an episode's script with ElevenLabs and generate its sound effects. This is clearly distinguishable from siblings like render_stills, render_take, and list_voices, so an agent can identify the tool's job without opening the schema.

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 implies the usage context (voicing an episode's script lines and generating SFX), but it never states when to use this versus alternatives or prerequisites such as needing voices to exist first. There is no explicit when/when-not guidance or named alternative.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.