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ti-nspire-mcp

ti-nspire-mcp

by reliasdomi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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generate_python_template

Generate ready-to-use, optimized Python code templates for TI-Nspire CX II, including math solver, graphics, serial receiver, and notes viewer options.

Instructions

Genera plantillas de código listas y optimizadas para el entorno Python de la TI-Nspire CX II.

:param template_type: 'math_solver', 'graphics', 'serial_receiver' o 'notes_viewer'

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": "generate_python_template"
  }
}

Input Schema

NameRequiredDescriptionDefault
template_typeNomath_solver

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full behavioral burden, yet it never says whether the tool returns a code string or writes a file, whether any existing document is touched, or what permissions/environment are required. For a generator positioned next to document-creation tools, that ambiguity is the most consequential gap.

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?

Two short lines with the purpose front-loaded and no filler. The ':param' docstring fragment restates the schema property name and is slightly redundant, but it is the only place the allowed values appear, so it earns its space.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple (one optional parameter, and an output schema exists so return values need no explanation), and the description covers purpose and valid values. It is still incomplete on the one thing that matters most here: output form (code snippet vs. file/document) relative to the nearby creation tools.

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% and the schema defines no enum, so naming the four allowed values is genuine added value beyond the schema. However it doesn't explain what each template contains or mention the documented default ('math_solver'), leaving the parameter only half-described.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Genera plantillas de código') plus the exact target runtime ('entorno Python de la TI-Nspire CX II'), which separates it from file-creation siblings such as create_python_tns_document. It stops short of naming any sibling explicitly, so an agent must infer that this produces template code rather than a document.

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?

The list of template_type values implicitly tells the agent which scenarios the tool covers (math solving, graphics, serial receiving, notes viewing), which is a weak form of when-to-use guidance. There is no explicit statement of when to prefer this over create_python_tns_document or convert_script_to_tns, and no 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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