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Glama

check_subscription

Retrieve your ElevenLabs subscription plan, credits used and left, and quota reset date to monitor account usage and limits.

Instructions

Plan, credits used and left, and when the quota resets.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden, and it discloses nothing beyond the field list: no statement that it is read-only, no auth/plan prerequisites, no rate-limit or freshness notes. The name implies a safe read, but that is inference, not disclosure.

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?

A single terse sentence with no filler or repetition, and the key concept (plan) is front-loaded. It is grammatically a fragment rather than a complete statement, but nothing is wasted.

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?

For a zero-parameter tool with no output schema, the description usefully enumerates what comes back (plan, credits used/remaining, quota reset timing), which is the main thing an agent needs. It omits usage context and any behavioral notes, keeping it short of 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?

The tool takes zero parameters, so the baseline is 4. There are no inputs whose semantics could be clarified, and the description's field enumeration maps to outputs rather than parameters.

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

Purpose3/5

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

The description is a noun phrase enumerating returned fields ('Plan, credits used and left, and when the quota resets') rather than stating a verb+resource action. Combined with the name check_subscription, an agent can infer it retrieves subscription/usage status, but the description itself never says what the tool does. No sibling overlap exists, so differentiation isn't the gap.

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 call this tool, no prerequisites, and no alternatives named. Siblings like list_outputs or list_models are unrelated, but the description offers no context that would help an agent decide when a subscription check is warranted.

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