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awesome-student-ai-skills

awesome-student-ai-skills

by cuic19053-hue
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

list_school_templates

Lists built-in university-specific formatting templates for Chinese schools, covering standard margins, font sizes, and red-header layouts, so you can choose the correct style for applications.

Instructions

列出当前内置支持的高校特定排版样式模板。 支持清华、北大、浙大、武大等高校的标准页边距、字号和红头格式。

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": "list_school_templates"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It communicates that only currently built-in supported templates are listed and gives examples of their formatting properties, but it does not explicitly confirm read-only safety, side-effect behavior, or availability constraints.

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 two concise sentences with no wasted language. It front-loads the core action and then adds useful examples of supported formatting details.

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?

For a zero-parameter list tool with an output schema, the description is nearly complete: it explains what is listed and gives examples of supported template features. The main minor gap is that it does not explicitly relate this tool to document generation workflows or state that results are limited to built-in templates only.

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 there is no parameter semantics burden. A baseline of 4 is appropriate because the description does not need to explain inputs, and it correctly focuses on the resource being listed.

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: listing built-in university-specific typesetting style templates. It also clarifies scope with examples of supported universities and formatting aspects, making it clearly distinct from sibling tools such as generate_student_doc or skill-related tools.

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

Usage Guidelines3/5

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

Usage is implied: an agent would call this to discover available school templates, likely before generating a document. However, the description does not explicitly state when to use it versus alternatives such as generate_student_doc, nor does it mention any prerequisites or exclusions.

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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