hicar-mcp

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by HICAR-Model

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Python

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get_physics_schemes

List available physics schemes for a given category, including codes, originating constants, and support status.

Instructions

List selectable schemes for a category (or selector like 'mp'), with codes, originating constants, and supported status.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "category": "<category>"
    },
    "name": "get_physics_schemes"
  }
}

Input Schema

Name	Required	Description	Default
`category`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jun 25, 2026

TDQS

A3.6/5.0

Behavior3/5

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

With no annotations, the description carries the full burden. It implies read-only behavior (listing) but does not explicitly state it, nor does it disclose any side effects, permissions, or rate limits. The mention of output fields provides some transparency, but lacks a clear behavioral statement.

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 a single, well-structured sentence that front-loads the action ('List selectable schemes...') and efficiently conveys the key points without any unnecessary words.

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 parameter, output schema present), the description is mostly complete. It outlines the output contents and the role of the category. However, it could briefly mention that the category comes from list_physics_categories to fully contextualize the input.

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?

Schema description coverage is 0%, so the description must compensate. It clarifies that 'category' can be a category name or a selector like 'mp', and that it determines which schemes are listed. However, it does not explain the allowed values, format, or how it relates to list_physics_categories, leaving room for ambiguity.

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 selectable schemes for a given category, specifying the output includes codes, originating constants, and supported status. It distinguishes from sibling tools like list_physics_categories (which lists categories) and resolve_physics_scheme (which resolves a specific scheme).

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

Usage Guidelines2/5

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

The description only explains what the tool does, not when to use it or alternatives. It offers no guidance on prerequisites, context, or trade-offs with sibling tools like resolve_physics_scheme or list_physics_categories. The agent is left to infer usage.

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