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get_usage

Check remaining Claude subscription capacity in the 5-hour and weekly usage windows before launching large fleets or switching to stronger models. Shows utilisation percentages and reset times.

Instructions

How much of the Claude subscription is left: the 5-hour and weekly windows.

Worth a look before opening a large fleet, and when deciding whether to run the stronger model everywhere. Percentages are utilisation, so 100 means spent; resets_at says when the window rolls over. Unavailable (no local credentials, or the endpoint refused) comes back as ok: false rather than a made-up number.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_usage"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.3Oct 21, 2026

TDQS

A4.5/5.0

Behavior5/5

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

With no annotations, the description carries the full burden and does it well: it defines the metric direction ('percentages are utilisation, so 100 means spent'), the meaning of resets_at, and the failure mode ('Unavailable... comes back as ok: false rather than a made-up number'). That last disclosure is exactly the kind of non-obvious behaviour an agent needs to avoid misreading a degraded result as real data.

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 the core answer in the first clause, then rationale, then edge-case semantics. Slightly verbose in the middle sentence and split across hard line breaks, but every sentence carries distinct information.

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?

An output schema exists, so return values need not be spelled out, yet the description still supplies the interpretation layer (units, direction, resets_at, error signalling). The only real gap is the format/timezone of resets_at, which an agent must read from the output schema to act on.

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 there is nothing for the description to disambiguate; the baseline for a 0-parameter tool is 4. No parameter-related content is missing.

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?

States a specific resource and scope: 'How much of the Claude subscription is left: the 5-hour and weekly windows.' That is a concrete verb+resource (read remaining subscription quota across two named windows) and is unambiguously distinct from every sibling, which deal with profiles, sessions, terminals, and worktrees.

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?

Gives concrete usage conditions: 'Worth a look before opening a large fleet, and when deciding whether to run the stronger model everywhere.' Two real decision points, but it names no alternative tool and states no when-not-to-use case, so it stops short of explicit routing.

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