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learn-hmr-basics

learn-hmr-basics
Read-only

A brief and concise explanation of the hmr library.

This tool provides information on how to use reactive programming or use hot module reloading in Python. As long as the user mentions HMR / Reactive Programming, this tool must be called first! Don't manually view the resource, call this tool instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.2/5.0
Behavior3/5

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

The readOnlyHint annotation already communicates the safe read-only nature. The description adds that it is a 'brief and concise explanation,' which hints at output size, but it does not disclose other behavioral traits like rate limits, auth requirements, or return format. It does not contradict the annotation, but adds limited value beyond it.

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 very concise: two short sentences plus a directive. It is front-loaded with the purpose, then gives usage guidelines and an alternative. Every sentence earns its place—no filler or repetition.

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 (0 params, no output schema, read-only annotation), the description covers the core facts: what it does, when to use it, and the nature of the output ('brief and concise explanation'). It does not explicitly state the output format, but 'explanation' strongly implies textual content. For this complexity level, it is sufficiently 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 has zero parameters, and the empty schema fully covers this. Per the rubric, a 0-parameter tool gets a baseline of 4. The description does not need to explain parameters, as there are none.

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 explicitly states it is 'A brief and concise explanation of the hmr library' and that it provides information on reactive programming/HMR in Python. This is a specific verb-resource pairing that distinguishes it from sibling tools like view-hmr-core-sources and view-hmr-unit-tests, which are likely source/tests viewers. The instruction to call this tool first further sets it apart.

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 gives a clear when-to-use condition: 'As long as the user mentions HMR / Reactive Programming, this tool must be called first!' It also provides an alternative: 'Don't manually view the resource, call this tool instead.' However, it does not explicitly name sibling tools or describe when not to use this tool beyond the manual-viewing alternative.

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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TDQS

A4.3/5.0
Disambiguation4/5

Each tool provides a distinctly different type of content: conceptual overview, source code, and usage examples. The purposes are clear, though the distinction between viewing core sources and unit tests is somewhat subtle as both are code.

Naming Consistency5/5

All tool names follow a consistent verb-noun pattern with hyphens (learn-hmr-basics, view-hmr-core-sources, view-hmr-unit-tests), making the naming predictable and easy to understand.

Tool Count5/5

With 3 tools, the server is well-scoped for its purpose of educating users about the HMR library. Each tool covers a necessary aspect - explanation, implementation, and examples - without any redundancy.

Completeness5/5

The server provides a complete learning path for the HMR library: a conceptual introduction, the full core source code, and unit tests demonstrating usage. There are no obvious gaps in this educational scope.