ElevenLabs MCP Server

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Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool targets a distinct operation within the ElevenLabs ecosystem (agents, voices, speech, music, etc.) with detailed descriptions that clearly differentiate them. No two tools appear to do the same thing.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using snake_case. There are no abbreviations or style mixing.
Tool Count4/5
With 26 tools, the server is comprehensive but somewhat heavy. However, each tool corresponds to a distinct ElevenLabs feature, and the number is appropriate given the breadth of the API. A few tools like search_voice_library and search_voices could be merged, but overall the scope warrants the count.
Completeness4/5
The tool set covers the main features of ElevenLabs (text-to-speech, voice cloning, music generation, agents, calls) adequately. However, there are gaps such as missing update/delete tools for agents, voices, and knowledge bases, which slightly reduces completeness.
Average 3.8/5 across 26 of 26 tools scored. Lowest: 3/5.
See the Tool Scores section below for per-tool breakdowns.
This repository is archived. Archived repositories automatically receive an F maintenance tier.
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and openWorldHint=true. The description adds minimal behavioral context beyond stating it gets details; no mention of caching, permissions, or return format details beyond what output schema provides.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single 11-word sentence with no wasted words, but it could be more informative without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 required param, output schema exists), the description is minimal. It lacks guidance on when to use it, what details are included, or prerequisites, making it incomplete for an AI agent to use reliably.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one required parameter 'agent_id' with 0% description coverage. The description does not explain what agent_id is or how to obtain it, failing to compensate for the schema's lack of documentation.
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 verb 'Get details' and the resource 'specific conversational AI agent', effectively distinguishing it from siblings like list_agents (which lists all agents) and create_agent (which creates).
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?
No explicit when-to-use or alternatives are provided; the intended usage is implied by the tool's purpose (fetch details for a single agent) but lacks explicit guidance or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description's simple statement is consistent. No additional behavior is disclosed, but none is needed for a straightforward read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence. It is efficient but could be slightly more informative without becoming verbose.
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?
For a simple retrieval tool with one parameter and an output schema, the description is adequate. However, it lacks usage context relative to sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the voice_id parameter or its format beyond the schema. The phrase 'specific voice' implies an identifier but adds no concrete meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves details of a specific voice, but does not differentiate from sibling tools like search_voices or voice_clone. The verb and resource are clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., search_voices). The description does not mention prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description contradicts annotations: readOnlyHint=true but the tool makes a paid API call and saves files, implying mutation. Description adds cost warning and file creation details, but the contradiction undermines reliability.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with purpose, includes naming convention and example. Each sentence provides useful information, though the cost warning could be integrated more succinctly.
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?
Output schema exists, so return values are not required. However, description omits what the tool returns (likely file paths) and does not explain the three previews' variations fully. Adequate but with gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so description must explain parameters. It partially explains 'text' and 'output_directory' but does not describe the required 'voice_description' parameter beyond its name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Create voice previews from a text prompt' and specifies three previews with variations. However, it does not differentiate from siblings like 'text_to_speech' or 'create_voice_from_preview'.
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?
Explicitly warns about cost and directs to use only when user requests. Includes context about auto-generation when no text provided, but does not mention exclusions or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description states the tool makes an API call and saves a file, implying a mutation. However, the annotation readOnlyHint=true indicates a read-only operation, creating a direct contradiction. Additionally, the openWorldHint adds further confusion. Score 1 per guideline for contradiction.
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 sentences with no redundant information. Every sentence adds value: the first defines the action, the second provides a critical usage warning. Very concise and well-front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema (not shown), the description lacks details on return format, file types, or behavioral nuances. The contradiction with annotations further reduces completeness. The tool is simple but still requires more context for safe invocation.
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 0%, so the description must compensate. It adds meaning for output_directory by specifying the default ($HOME/Desktop), but input_file_path remains unexplained (relies on param type 'string'). Partial compensation leads to a score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Isolate audio from a file' which is a specific verb+resource. While it distinguishes from sibling tools like speech_to_text or compose_music, it doesn't elaborate on what 'isolate' entails (e.g., vocals from background). The action is unambiguous enough for selection.
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?
The description includes a cost warning and explicitly states 'Only use when explicitly requested by the user', providing clear context for usage. However, it does not specify when NOT to use it or list alternative tools for similar tasks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint: true, but the description does not elaborate on side effects (e.g., audio playback) or system requirements. Since annotations already cover basic behavioral intent, a moderate score is appropriate.
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?
Two sentences deliver the core purpose and format support with no extraneous words. Ideal brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has one required param and an output schema, yet the description omits return behavior, required permissions, or playback context. Incomplete for an agent to fully understand usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter (input_file_path) with no description, and the description does not explain it. With 0% schema coverage, the description fails to compensate.
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's function: 'Play an audio file.' It specifies supported formats (WAV and MP3), distinguishing it from sibling tools like text_to_speech or compose_music.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like speech_to_text or text_to_sound_effects. It lacks prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description states 'Saves output file' indicating a write operation, but annotations include readOnlyHint: true, which suggests no side effects. This is a direct contradiction, meriting a score of 1.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with front-loaded purpose, but could benefit from structured parameter descriptions. The cost warning adds useful context without being verbose.
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?
Given the tool has an output schema, the description does not need to explain return values. It covers basic functionality and output directory, but lacks details on output format or error handling. Adequate but could be more complete.
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 coverage is 0%, but the description adds meaning by specifying that input_file_path should be audio files and that output_directory has a default of $HOME/Desktop. However, it does not fully explain all parameters (e.g., voice_name).
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 transforms audio from one voice to another using provided audio files, which is a specific verb and resource. It implicitly distinguishes from siblings like text_to_speech or voice_clone by focusing on voice transformation.
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 warns about costs and says to use only when explicitly requested, but does not explicitly state when not to use or mention alternative tools. Usage guidance is implied but incomplete.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate openWorldHint: true, and the description adds explicit context about external API calls to ElevenLabs and potential costs. This goes beyond annotations, though some traits like file format requirements are omitted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences plus a warning are concise and front-loaded. The warning is clearly separated, but structure could be improved with bullet points or parameter details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 3 parameters and no output schema shown, the description lacks necessary details like audio format, length limits, and return value. It is insufficient for proper invocation given the complexity of voice cloning.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description fails to explain what 'files' (paths, URLs?), 'name', or 'description' mean. No parameter details are provided, leaving critical gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Create an instant voice clone of a voice using provided audio files,' specifying the verb and resource. It is distinct from sibling tools like text_to_voice or create_voice_from_preview, though it does not explicitly differentiate.
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 includes a cost warning and advises to use only when explicitly requested, but it does not provide when-not-to-use guidance or compare to alternative tools like search_voices or text_to_voice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does 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.
Conciseness5/5
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.
Completeness3/5
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.
Parameters4/5
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.
Purpose4/5
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.
Usage Guidelines2/5
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.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description claims 'List all phone numbers' but the annotation openWorldHint=true indicates the result set may not be complete. This contradiction misleads the agent into assuming exhaustiveness. The description adds no other behavioral context beyond what annotations already provide.
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 a single sentence that immediately conveys the purpose with no extraneous words. It is front-loaded and efficient.
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?
Without considering the contradiction, the description is sufficient for a zero-parameter list tool with output schema present. However, the contradiction undermines completeness by providing false assurance of completeness. Also lacks mention of what fields are returned, though output schema may cover that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, and schema coverage is 100% (trivially). The description does not need to add parameter details. Baseline 4 applies per guidelines for zero parameters.
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 action ('List all phone numbers') and the resource ('associated with the ElevenLabs account'), making it distinct from sibling tools like list_agents or list_conversations. The verb and resource are specific and unambiguous.
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?
No guidance on when to use this tool versus alternatives. However, given the simple nature (no parameters, clear listing), implicit usage is straightforward. A higher score would require explicit context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and openWorldHint=true. The description adds no extra behavioral details (e.g., pagination limits, data freshness, or the implications of openWorldHint), failing to provide value beyond the annotations.
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 concise, with a clear purpose sentence followed by a structured parameter list. Every sentence earns its place, and it is front-loaded.
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?
Given the existence of an output schema and sibling tools, the description is moderately complete. It specifies return type ('TextContent about shared voices') but lacks context on open world behavior and differentiation from 'search_voices'. It is minimally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema description coverage, the description provides meaningful parameter semantics: explaning page indexing, page size range, and search term usage. This adds significant value over the bare schema, though more detail (e.g., search behavior) would improve it.
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 'Search for a voice across the entire ElevenLabs voice library,' specifying the verb, resource, and scope (entire library), which distinguishes it from sibling tools like 'search_voices'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 (e.g., 'search_voices'). The description only lists parameters without contextual usage tips.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint (safe read) and openWorldHint. The description adds return type info but does not disclose pagination behavior or potential rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Starts with a clear purpose, then returns and usage hint, then parameter list. No unnecessary words, though parameter descriptions could be integrated more concisely.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all 6 parameters with defaults and filtering logic. Output schema exists, so details on return format are not required. Pagination cursor is mentioned but behavior not elaborated.
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?
With 0% schema description coverage, the description lists each parameter with a brief functional description. These are minimal but add essential meaning beyond schema field names.
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 'Lists agent conversations' with a specific verb and resource. It distinguishes from siblings like 'get_conversation' which retrieves a single conversation.
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?
Provides a usage cue 'Use when: asked about conversation history' but lacks explicit when-not-to-use or alternatives such as 'get_conversation' for single conversations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description states the tool saves output files, implying a write operation, which contradicts the readOnlyHint annotation indicating the tool is read-only. This is a direct contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a front-loaded summary, constraints, and cost warning. The arg list is detailed but not excessively verbose. Slightly long but efficient for the complexity.
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?
Covers parameters and warnings well, but fails to describe the output or return value (despite an output schema existing). The contradiction with annotations also reduces completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema description coverage, the description thoroughly explains each parameter, including default values, allowed ranges, and format options (e.g., output_format details). This adds significant value beyond the schema.
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 converts text descriptions of sound effects to audio files with specified duration. It specifies default output directory and constraints. Differentiates from siblings like text_to_speech by focusing on sound effects.
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?
Provides explicit cost warning and instructs to use only when explicitly requested. However, it lacks explicit comparison to sibling tools or guidance on when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, covering the behavioral baseline. The description adds nothing beyond stating 'list all available', which is consistent but does not enrich the agent's understanding of traits like auth, rate limits, or interpretation of 'available'.
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 a single sentence that is clear, front-loaded, and contains no wasted words. It earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters, output schema present, and annotations already covering open-world and read-only hints, the description is adequate. One might wish for clarification on 'available' scope, but overall it is complete for this simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, so the description does not need to add param information. Schema coverage is 100% trivially. The description is sufficient for a param-less tool.
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 lists all available conversational AI agents, with a specific verb and resource, and it distinguishes itself from siblings like get_agent and create_agent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like get_agent or list_conversations. No exclusions or contextual hints are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description claims the tool generates and saves output files, contradicting the readOnlyHint=true annotation which implies no side effects. This is a serious inconsistency. Additionally, no mention of permission needs or reversibility.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured: purpose, output location, constraints, args list, then cost warning. Concise but informative; slight redundancy in repeating default output directory.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers constraints, parameters, output, and cost. However, the annotation contradiction reduces completeness in behavioral transparency. Output schema exists so return values are handled.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, the description thoroughly explains all 5 parameters: input_file_paths (order preserved), description, tags (max 10), model_id (enum with defaults), output_directory. Adds meaning beyond schema.
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 'Generate background music for one or more video files' with explicit constraints and output location, distinguishing it from sibling tools like compose_music or text_to_sound_effects.
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?
Provides explicit constraints (1-10 videos, size/duration limits) and a cost warning indicating when to use ('Only use when explicitly requested by the user'), though no explicit alternative tools are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, but description reveals side effects: saves files, stores song server-side for inpainting, and incurs costs. This contradiction reduces transparency score to 1.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-organized with sections and front-loaded purpose. Slightly redundant sentences about output directory, but overall efficient for the complexity.
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?
Given 8 parameters, two models, inpainting workflow, and output schema present, the description covers all necessary context: defaults, model differences, parameter constraints, and cost warning. No gaps for agent decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description explains all 8 parameters in detail, including composition plan structure per model, default paths, and constraints like music_length_ms bounds. Fully compensates for schema gap.
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?
Clearly states 'Convert a prompt to music and save the output audio file to a given directory' with specific verb and resource. Distinguishes from sibling audio tools by focusing on music composition and two models.
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?
Provides usage context: must provide prompt or composition_plan, defaults, and cost warning to use only when explicitly requested. Could be more explicit about when not to use but reasonably covers alternative models and inpainting requirements.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description contradicts annotations: readOnlyHint=true suggests no side effects, but the description states it saves a file and makes an API call incurring costs. Per instructions, score 1 for contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is long but well-structured: purpose first, then cost warning, then parameter list in order. Every sentence adds value, though some details (e.g., output_format options) could be more concise. Front-loading is effective.
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?
Given 12 parameters, 1 required, and existing output schema, the description is comprehensive. It covers side effects (file saving, cost), parameter choices, defaults, and return types (file path or MCP resource). No gaps identified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries full burden. It provides detailed explanations for all 12 parameters, including ranges (e.g., speed 0.7-1.2), defaults, options for model_id and output_format, and semantics for stability, similarity_boost, etc. This far exceeds 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 clearly states 'Convert text to speech with a given voice. Saves output file to directory.', providing a specific verb+resource and distinguishing it from sibling tools like speech_to_text, voice_clone, and text_to_sound_effects.
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?
Includes a cost warning and explicit instruction to only use when requested by the user, plus a constraint that only one of voice_id or voice_name can be provided. Lacks explicit when-not-to-use or alternatives, but the cost warning provides strong guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate non-destructive and open-world behavior. Description adds value by explicitly stating it makes an API call to ElevenLabs, which may incur costs. No contradictions with annotations.
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?
Two sentences plus a cost warning note. Front-loaded with purpose and key usage constraint. Every sentence serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Description covers purpose, source of key parameter, and cost warning. Output schema exists to handle return value details. Minor gap: does not explain prerequisites like having a preview from `text_to_voice`.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 0% description coverage. Description adds meaning for `generated_voice_id` by linking to `text_to_voice`, but provides no guidance on `voice_name` or `voice_description`. Insufficient compensation for low schema coverage.
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?
Description clearly states the tool 'adds a generated voice to the voice library' and specifies it uses the voice ID from the `text_to_voice` tool. Verb and resource are specific, and the reference to a sibling distinguishes its purpose.
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?
The cost warning and instruction 'Only use when explicitly requested by the user' provide clear usage context. However, it does not explicitly list when not to use or name alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already set destructiveHint=false and openWorldHint=true. The description adds that it makes an API call and may incur costs, but does not elaborate on failure modes or side effects beyond creation. Adequate but not exceptional.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively long due to the parameter list, but it is well-structured with a front-loaded cost warning and a clear 'Args:' section. Every sentence adds value given the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists, the description does not need to explain return values. It covers creation behavior, parameter constraints, and usage conditions. Missing information about error handling or validation, but overall complete for its purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries full burden. It provides detailed explanations for all 17 parameters, including defaults, ranges, and meanings (e.g., temperature range, stability range, turn_timeout default). This fully compensates for the missing schema descriptions.
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 'Create a conversational AI agent with custom configuration', which is a specific verb + resource. It distinguishes from siblings like 'add_knowledge_base_to_agent' and 'get_agent' by focusing on creation.
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?
The description includes a cost warning that tells the agent to only use when explicitly requested by the user, providing a clear usage condition. It does not explicitly mention alternatives, but the warning effectively guides when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and openWorldHint=true, so the description adds value by detailing search behavior (fields searched) and a caveat about sort field 'created_at_unix' possibly missing. This is sufficient behavioral disclosure beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the purpose. However, it redundantly states 'Searches in name, description, labels and category' both in the main description and the search param docstring. Minor redundancy, but overall well-structured.
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 description covers search functionality and sorting, and an output schema exists for return values. However, it lacks information on pagination, result limits, case sensitivity, or matching behavior. Given the tool's simplicity and the openWorldHint, this is adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, the description compensates well by explaining each parameter: 'search' describes the search fields, 'sort' notes a potential issue with older voices, and 'sort_direction' clarifies order. This adds context that the schema alone does not provide.
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 searches for voices already added to the user's ElevenLabs voice library, specifying the verb 'search' and the resource 'voices in user's library'. It also lists searchable fields (name, description, labels, category), differentiating it from the sibling 'search_voice_library' which likely searches public voices.
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?
The description provides clear context: it searches the user's own voice library across multiple fields. While it doesn't explicitly state when not to use it or compare to alternatives, the scope is well-defined, and the sibling name 'search_voice_library' implies a different usage. Minor lack of explicit exclusions prevents a perfect score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint. The description adds the behavioral hint that the tool can measure usage, which provides some extra context but is not required. It does not contradict annotations.
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 sentences, no filler words, and front-loads the core purpose. Every word adds value.
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?
Given the simplicity (no parameters, output schema present), the description fully covers what the tool does and offers a relevant use case, leaving no significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters (schema coverage 100%), so the baseline is 4. The description adds no parameter details, but none are needed.
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 checks the current subscription status, with a specific verb and resource. It also adds a practical use case ('measure the usage of the API'), distinguishing it from sibling tools which are unrelated.
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?
The description provides a clear context for use (measuring API usage) but does not explicitly state when not to use or name alternatives. Since no sibling tools overlap in functionality, this is adequate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide destructiveHint=false and openWorldHint=true. The description adds behavioral context: cost implications, enterprise gating, and return of song_id for downstream use. This exceeds annotation coverage without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear paragraphs, an Args block, and a prominent cost warning. It front-loads the primary purpose and is appropriately sized, though some minor redundancies could be trimmed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown), the description adequately covers purpose, usage, parameters, cost, and enterprise restrictions. It omits file format or size limits but remains comprehensive for a simple 2-parameter tool with open-world hint.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description's Args section explains both parameters: input_file_path as local file path, extract_composition_plan with default 'music_v2' and possible values. This adds meaningful guidance beyond the schema's minimal type/title.
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 uploads an audio file to ElevenLabs for inpainting workflows, returns a song_id for use in compose_music, and optionally extracts a composition plan. It distinguishes from sibling tools like compose_music and isolate_audio by specifying its unique upload and reference purpose.
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?
The description explains when to use the tool (for inpainting workflows, optionally extracting composition plan) and includes a cost warning and enterprise gating note. However, it does not explicitly state when not to use it or mention alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate non-destructive and open-world. Description adds cost warning and allowed file types, going beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is clear and structured with a cost warning and parameter list. Slightly verbose due to Args, but effective overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, usage, parameters, and file types. With output schema present, return values need not be described. Missing details on how multiple sources interact, but still complete enough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the Args section explains each parameter clearly (agent_id, knowledge_base_name, url, file, text), providing full meaning.
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?
Clearly states 'Add a knowledge base to ElevenLabs workspace' and specifies allowed file types. Distinguishes itself from sibling tools like create_agent or speech_to_text.
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?
Includes a cost warning and explicit instruction to use only when user requests it. Does not mention when not to use or alternatives, but provides sufficient context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate destructive and open-world hints. The description adds specifics: automatic provider detection and a cost warning about ElevenLabs API calls. This extends beyond annotations but does not detail all behavioral traits (e.g., call duration, error handling).
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 very concise, front-loaded with the purpose, followed by a cost warning and parameter list. No redundant sentences; every word adds value. The structure is clear and easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and presence of an output schema, the description adequately covers key aspects: purpose, parameters, return type, and cost implications. However, it lacks context on prerequisites (e.g., agent setup) or error scenarios, leaving some gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description provides textual explanations for all three parameters (agent_id, agent_phone_number_id, to_number), including the expected format for to_number. This adds critical meaning beyond the schema, though descriptions are minimal and could include where to obtain IDs.
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's purpose: making an outbound call using an ElevenLabs agent. It specifies the action ('make'), resource ('ElevenLabs agent'), and includes automatic provider detection, which is a distinctive feature. The tool is unique among siblings as no other tool performs outbound calling.
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?
The description includes a cost warning and explicitly states 'Only use when explicitly requested by the user,' providing a clear usage constraint. However, it does not mention when not to use this tool or suggest alternatives, though the sibling list implies uniqueness.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true and openWorldHint=true, and the description confirms no credit cost and details output shapes. This provides sufficient transparency beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a summary, usage note, return shape details, and parameter list. Each sentence adds value, though slightly verbose.
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?
Given no output schema, the description provides detailed return shapes for both model variants. It covers all parameters and usage context, making it complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by explaining each parameter, including the range for music_length_ms and the model_id enum values.
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 'Create a composition plan for music generation' and explains how it differs from sibling tools like compose_music, including the relationship between planning and generation.
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?
The description mentions it costs no credits but is rate-limited, and that the plan can be used with compose_music. It also explains optional parameters like source_composition_plan, but does not explicitly state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint (true) and openWorldHint (true). The description adds value by specifying that the tool retrieves completed conversations and returns conversation details plus full transcript, which is behavioral context beyond the annotations.
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 extremely concise at three sentences, each serving a distinct purpose: stating what it does, when to use it, and describing the argument. No redundant or irrelevant information.
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?
Given low complexity (1 parameter, presence of output schema indicating return structure is documented elsewhere), the description adequately covers purpose, usage, parameter source, and general return content. No gaps remain for this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explains the only parameter (conversation_id) as 'the unique identifier of the conversation to retrieve' and directs the agent to list_conversations to get IDs, adding significant meaning beyond the schema (which only provides title and type).
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 'gets a conversation with transcript', specifying the resource (conversation) and the full transcript. It distinguishes from siblings like list_conversations by referencing it for obtaining IDs, and from get_agent which targets a different resource.
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?
The description provides explicit usage context: 'Use when: analyzing completed agent conversations.' It does not explicitly state when not to use, but implies this use case. The mention of list_conversations as a source for IDs provides a clear alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses API call and potential costs, and explains output behavior for both save and return modes. Annotations include readOnlyHint=true, which is consistent with not modifying input; description adds useful context beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with purpose, warning, args, and returns. Slightly lengthy but every sentence adds value. Front-loaded with core purpose.
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?
Covers all aspects: purpose, usage conditions (cost), parameters, return values, output location. With output schema present, description complements it well without redundancy.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description thoroughly explains each parameter including defaults, the meaning of diarize, and default output directory. Adds significant value beyond the raw schema.
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?
Description clearly states 'Transcribe speech from an audio file.' Specific verb and resource. Differentiates from sibling tools like speech_to_speech or text_to_speech.
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?
Includes cost warning and explicit instruction to use only when requested. Explains when save vs return modes apply. No explicit alternatives mentioned, but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that the tool makes an API call to ElevenLabs which may incur costs, and describes the full process of running the conversation and returning transcript plus analysis. Annotations (openWorldHint, destructiveHint) are consistent; no contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (args, warning) and examples, but is slightly verbose. Every sentence adds value, though could be trimmed slightly without losing substance.
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?
Given the 5 parameters and existence of an output schema, the description covers all necessary details: purpose, usage, parameter semantics, and behavioral context. It is fully complete for an agent to correctly select and invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by explaining each parameter: agent_id, simulated_user_prompt (with example), first_message, extra_evaluation_criteria (with structure and example), and max_turns (default 10). Adds significant meaning beyond the schema.
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 simulates a text conversation between an AI agent and a simulated user, returning transcript and analysis. It distinguishes from sibling tools like make_outbound_call and list_conversations by focusing on testing without a live call.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: 'test agent behaviour, evaluate prompts, and catch failure modes without a live call.' Includes a cost warning and instructs 'Only use when explicitly requested by the user,' providing clear usage boundaries.
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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