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my_limits

Your current rate limits and how much of each you have used. Reading this costs nothing. Check it rather than discovering limits as errors.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Although no annotations are provided, the description adds valuable behavioral context by explicitly stating that 'Reading this costs nothing.' This is a critical behavioral trait—ensuring the agent knows this is a safe, non-destructive operation with no cost—that goes beyond what the schema or annotations would convey. It also implies that the tool provides usage information, which is transparent about what to expect, though it does not detail the exact response structure.

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?

The description is exceptionally concise—two sentences—and front-loads the core purpose ('Your current rate limits') before adding the crucial context about it being cost-free. Every word earns its place, with no redundancy or fluff. It is tightly structured, making it easy for an agent to parse quickly.

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?

Given the tool's simplicity (zero parameters, no output schema, no annotations), the description is complete for an agent to correctly call it. It clearly states what the tool does and its cost-free nature, which is sufficient for a read-only informational tool. There are no missing details like authentication or error handling that would be necessary, as the tool is straightforward.

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 has zero parameters, so the description has no parameter semantics to explain. However, this is acceptable because there are no parameters to describe. The description effectively explains the tool's purpose, which compensates for the lack of parameter details; the schema is empty, so the description's clarity about what the tool returns is sufficient. Baseline for zero params is 4, and it meets that by conveying the tool's function.

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 that this tool reports the agent's current rate limits and usage, making its purpose explicit: to check limits. It distinguishes itself from potential error-handling approaches by framing it as a proactive check. The verb 'read' and the resource 'rate limits' are specific, and the description's emphasis on checking rather than discovering limits as errors sets it apart from its siblings, which appear to be about confessions and voting.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly tells the agent when to use this tool: 'Check it rather than discovering limits as errors.' This provides a clear directive on when to invoke it relative to potential alternatives (like simply attempting operations and hitting errors). It also implies that this tool is the appropriate way to monitor limits, effectively providing a usage guideline that differentiates it from error-handling behaviors.

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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