Check RunAPI pricing for ElevenLabs models and endpoints such as speech-to-text and text-to-speech before making API calls.
Look up RunAPI pricing for the elevenlabs model line.
| Name | Required | Description | Default |
|---|---|---|---|
| model | No | Model slug. Defaults to the line's primary model. | |
| action | No | Endpoint name. Defaults to the endpoint that offers the model. |
Changes observed during successful MCP inspections.
v0.2.0Input schema / additionalPropertiesRemoved value: -falseInput schema / properties / model / enumRemoved value: -[
- "audio-isolation",
- "speech-to-text",
- "text-to-dialogue-v3",
- "sound-effect-v2",
- "text-to-speech-multilingual-v2",
- "text-to-speech-turbo-v2.5"
-]v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. 'Look up' implies a non-destructive read and the 'elevenlabs model line' restriction usefully bounds scope, but nothing is said about authentication, whether prices are live or cached, units/currency, or what a lookup costs in rate limits. It discloses a little beyond the structured fields but not enough for a no-annotation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence with zero filler, front-loaded with the verb and the scope constraint. Nothing needs to be trimmed and nothing is buried.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter, zero-required lookup tool with full schema coverage, the description covers the essential purpose but omits the return semantics (currency, unit basis, per-endpoint breakdown) that matter when no output schema exists. It is adequate but leaves the agent guessing about what a 'pricing' result contains.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so both parameters (model slug, action endpoint) and their defaults are already documented in the schema. The description adds no syntax, format, or defaulting nuance beyond that, so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb ('look up') and resource ('pricing') and scopes it to the 'elevenlabs model line', which distinguishes it from the sibling action tools (isolate_audio, text_to_speech, etc.) that perform work rather than quote prices. It is clear, though it does not explicitly say 'this returns cost information and performs no action', leaving the read-only nature implicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no when-to-use or when-not-to-use guidance, no mention of prerequisites, and no indication of when an agent should consult pricing versus simply invoking an endpoint. The scope phrase 'elevenlabs model line' hints at applicability but is not framed as usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.