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PavolKum

claude-quota-mcp

by PavolKum

quota_status

Check your own Claude and Codex usage limits and reset times to plan long-running work around quota resets and avoid interruptions.

Instructions

Check the agent's own usage limits so long-running work can be planned around resets - e.g. if a window resets soon with usage to spare, front-load heavy work now. Providers: 'claude' (5-hour and weekly percentages from the documented Claude Code statusline snapshot, no credential; the undocumented OAuth usage endpoint only when the host opted in via CLAUDE_QUOTA_ALLOW_OAUTH_ENDPOINT=1; transcript-estimate fallback) and 'codex' (latest server-issued rate-limit snapshot from local Codex rollout logs - exact numbers, freshness = Codex's last activity). Default 'all' reports both.

Input Schema

NameRequiredDescriptionDefault
providerNoall
response_formatNomarkdown

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations, the description carries the full behavioral burden and does so well: it discloses the data sources per provider, that the statusline snapshot needs no credential, that the OAuth endpoint is undocumented and gated behind CLAUDE_QUOTA_ALLOW_OAUTH_ENDPOINT=1, that there is a transcript-estimate fallback, and that Codex freshness equals the last activity in local rollout logs.

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?

Purpose and use case are front-loaded in the first sentence, with provider detail following. The nested parentheticals make the second sentence dense, but nearly every clause carries load-bearing information about data provenance and caveats.

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?

An output schema exists, so return values need not be described. The description covers the provider semantics, data sources, credential requirements, and freshness caveats an agent would need before invoking the tool, leaving no significant gap.

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%, so the description must compensate, and it does for the provider enum: it explains what 'claude' and 'codex' return, their provenance, and that default 'all' reports both. The response_format parameter is never mentioned, but its markdown/json enum is self-explanatory.

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 states a specific verb and resource ('Check the agent's own usage limits') and immediately frames the scope as the agent's own quota, not general account usage. It also distinguishes the tool's purpose from generic monitoring by tying it to planning long-running work around resets.

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?

It gives a concrete when-to-use scenario: front-load heavy work if a window resets soon with usage to spare. There are no sibling tools, so no alternatives need naming, but no explicit when-not-to-use condition is offered either.

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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