Retrieve all available models from ElevenLabs to select the right one for text-to-speech and audio processing tasks.
List all available models
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.2.1Output schema / (root)Previous value: -nullNew value: +{
+ "$defs": {
+ "McpLanguage": {
+ "properties": {
+ "language_id": {
+ "title": "Language Id",
+ "type": "string"
+ },
+ "name": {
+ "title": "Name",
+ "type": "string"
+ }
+ },
+ "required": [
+ "language_id",
+ "name"
+ ],
+ "title": "McpLanguage",
+ "type": "object"
+ },
+ "McpModel": {
+ "properties": {
+ "id": {
+ "title": "Id",
+ "type": "string"
+ },
+ "languages": {
+ "items": {
+ "$ref": "#/$defs/McpLanguage"
+ },
+ "title": "Languages",
+ "type": "array"
+ },
+ "name": {
+ "title": "Name",
+ "type": "string"
+ }
+ },
+ "required": [
+ "id",
+ "name",
+ "languages"
+ ],
+ "title": "McpModel",
+ "type": "object"
+ }
+ },
+ "properties": {
+ "result": {
+ "items": {
+ "$ref": "#/$defs/McpModel"
+ },
+ "title": "Result",
+ "type": "array"
+ }
+ },
+ "required": [
+ "result"
+ ],
+ "title": "list_modelsOutput",
+ "type": "object"
+}v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds that the tool lists 'all available' models, which is consistent. No additional behavioral context is needed beyond what annotations provide.
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?
The description is a single sentence with no unnecessary words. It is appropriately sized for the tool's simplicity.
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?
Given zero parameters and the presence of annotations and an output schema, the description is minimally adequate. It conveys the basic purpose but could benefit from clarifying what a 'model' is in this context.
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?
With zero parameters and 100% schema description coverage, the description does not need to add parameter semantics. A baseline of 4 is appropriate as there is no gap to fill.
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 'List all available models' clearly states the action (list) and resource (models). It is specific enough, though it does not differentiate from sibling tools, which are mostly unrelated.
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?
No guidance is provided on when to use this tool versus alternatives. While there are no obvious sibling tools for listing models, the description lacks any context on prerequisites or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.