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Chispa MCP

Chispa MCP

by jeffercbs
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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Cargar preguntas de quiz

add_quiz_questions

Loads multiple-choice questions into a lesson quiz from JSON or line-based text, up to 200 per call, with dry_run validation before saving.

Instructions

[Equipo del aula] Carga preguntas de opción múltiple en el quiz de una lección (hasta 200 por llamada). Envía questions (JSON) o questions_text (una por línea: «enunciado | opción | *correcta | opción | explicación: …»). Todo o nada; dry_run=true valida sin guardar.

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": {
      "classroom_id": "<classroom_id>",
      "session_id": "<session_id>"
    },
    "name": "add_quiz_questions"
  }
}

Input Schema

NameRequiredDescriptionDefault
dry_runNo
questionsNo
session_idYesLección
classroom_idYesAula
questions_textNoTexto compacto, una pregunta por línea

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare a non-readonly, non-destructive, closed-world write. The description adds real value with 'todo o nada' atomicity and dry_run validation, but omits what an agent most needs to know for a mutation: whether this appends to or replaces the existing quiz questions, and what authorization it requires.

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?

Three dense sentences with the resource and batch cap first, the two input modes second, atomicity and dry_run last. Nothing is repeated from the title and no sentence is filler.

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?

No output schema exists, yet the description covers limits, atomicity, validation mode, and the compact text syntax. The notable gap is append-vs-replace semantics of an existing quiz, which matters for a 5-parameter batch mutation even with safety annotations present.

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?

Schema coverage is 60%, and the description compensates by explaining the two mutually exclusive input channels and, crucially, the pipe-delimited line grammar for questions_text («enunciado | opción | *correcta | opción | explicación: …»), which the schema only gestures at as 'una pregunta por línea'.

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: carga preguntas de opción múltiple en el quiz de una lección, with a batch limit of 200. It is clear about scope, though it never names the single-item sibling save_quiz_question, leaving the batch-vs-single distinction implicit.

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?

Gives the invocation context (a lesson quiz, up to 200 at a time) and explains what dry_run does, but does not say when to choose this over save_quiz_question, import_exam, or import_module_content, nor when a caller should prefer questions_text over questions.

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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