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AIWerk

@aiwerk/mcp-server-elevenlabs

by AIWerk

list_environment_variables

Read-onlyIdempotent

Retrieve and filter ElevenLabs environment variables by type, label, or environment, with pagination for large result sets.

Instructions

List Environment Variables

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoFilter by variable type
labelNoFilter by exact label match
cursorNoPagination cursor from previous response
page_sizeNoNumber of items to return (1-100)
environmentNoFilter to only return variables that have this environment. When specified, the values dict in the response will only contain this environment.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.3/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is fully covered by structured fields. The description contributes nothing beyond that - it does not mention pagination behavior, the cursor/page_size interaction, or the special environment-scoping side effect on the response. No contradiction, but no added value either.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The single phrase is not bloated, but it is under-specified rather than concise - there is simply nothing to trim because nothing was said. It is front-loaded by default but carries no payload.

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?

For a five-parameter, paginated list tool with no output schema, the description should explain pagination via cursor, the meaning of page_size bounds, and the filter semantics. None of that appears, leaving the agent reliant entirely on the schema and annotations to call it correctly.

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%: all five parameters (type, label, cursor, page_size, environment) are documented in the schema, including the non-obvious note that 'environment' narrows the response values dict. Per the rubric, a fully-covered schema sets the baseline at 3; the description adds nothing on top of it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description is a verbatim restatement of the tool name and title, adding no distinguishing information. It does not differentiate from siblings such as get_environment_variable, create_environment_variable, or update_environment_variable, nor does it state scope (workspace/environment). This is the textbook 'tautology' case.

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?

There is no guidance on when to use this tool versus get_environment_variable (single fetch) or list_auth_connections. No prerequisites, no exclusions, no context about pagination-driven iteration. The agent must infer all routing decisions from the name alone.

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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