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ClockNext MCP Server

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by ClockNext

ClockNext: list models

clocknext_list_models

List the organisation's enabled models with USD prices per 1,000,000 tokens. Return modelId for usage verification; set active=true to see only meterable models.

Instructions

List the models the organisation has enabled, with their USD prices per 1,000,000 tokens. Use a returned modelId as the model when verifying or recording usage. Pass active=true to see only models that can be metered right now.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
activeNoOnly return currently-active (meterable) models.
Behavior4/5

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

With no annotations provided, the description carries the full transparency burden. It discloses that the tool lists only enabled models, includes prices, returns modelId for downstream use, and supports an active filter. While it does not mention pagination or output format, it adds meaningful behavioral detail beyond the bare schema.

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?

Three concise, front-loaded sentences: purpose, downstream usage hint, and parameter guidance. Every sentence adds value, with no redundant or filler content.

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 (one optional boolean parameter, no output schema), the description covers the essential aspects: what is listed, pricing, modelId usage, and the active filter. It lacks details on response structure or pagination, but these are not critical for this list operation.

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?

The schema already fully documents the single parameter `active` with 'Only return currently-active (meterable) models.' The description's 'Pass active=true to see only models that can be metered right now' adds minimal extra context ('right now'), so it does not significantly enhance the 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?

The description clearly states the tool lists enabled models with their USD pricing per million tokens, using a specific verb ('List') and resource ('models'). It distinguishes itself from sibling list tools by focusing on models and their prices, and ties the returned modelId to usage in verification/recording.

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: use the returned modelId for verifying or recording usage, and optionally pass active=true to filter for currently meterable models. It does not explicitly mention when not to use it, but the guidance is sufficient for the user to understand the tool's role.

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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