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marioluciofjr

MCP-Server de Mapas Mentais

by marioluciofjr
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Python
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intermediario

Generate intermediate-level mind maps to organize and visualize knowledge on any topic for better understanding and retention.

Instructions

Gera um mapa mental de conhecimentos intermediários sobre o tema.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
temaYes

Implementation Reference

  • server.py:69-69 (registration)
    Registers the 'intermediario' tool using the MCP decorator.
    @mcp.tool(name="intermediario")
  • server.py:70-77 (handler)
    The main handler function for the 'intermediario' tool. It takes a 'tema' string parameter and returns a formatted string prompt for generating intermediate-level mental maps on the topic.
    def intermediario(tema: str) -> str:
    """Gera um mapa mental de conhecimentos intermediários sobre o tema."""
    return (
        f"Conhecimentos intermediários sobre {tema}, focando somente nos tópicos abaixo:\n"
        f"- Analisar: identifica padrões, relacione ideias e compare conceitos.\n"
        f"- Avaliar: julga a eficácia, valide argumentos e critique resultados.\n"
        f"- Criar: propõe novas soluções, crie projetos ou sugira melhorias."
    )

Tool Definition Quality

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool generates a mind map, implying a read-only or creative operation, but doesn't clarify if it requires specific inputs beyond the topic, how the output is structured, whether it's cached or real-time, or any error conditions. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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, clear sentence in Portuguese: 'Gera um mapa mental de conhecimentos intermediários sobre o tema.' It is front-loaded with the core action and resource, with no wasted words. Every part of the sentence contributes to understanding the tool's purpose efficiently.

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

Completeness2/5

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

Given the tool has no annotations, no output schema, and low schema description coverage (0%), the description is incomplete. It doesn't explain what 'conhecimentos intermediários' (intermediate knowledge) means, how the mind map is returned (e.g., text, image, structured data), or any limitations. For a tool that likely produces complex output, more context is needed to use it effectively.

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?

The description mentions 'sobre o tema' (on the topic), which aligns with the single parameter 'tema' (topic) in the input schema. However, schema description coverage is 0%, so the schema provides no additional details about the parameter. The description adds minimal semantic context by implying the parameter is a topic string, but doesn't specify format, length, or examples. With one parameter and low coverage, this is adequate but basic.

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?

The description clearly states the tool's purpose: 'Gera um mapa mental de conhecimentos intermediários sobre o tema' (Generates a mind map of intermediate knowledge on the topic). It specifies the action (generate), the resource (mind map), and the scope (intermediate knowledge on a topic). However, it doesn't explicitly distinguish this tool from its siblings like 'inicial' or 'revisa', which might also be related to knowledge mapping or topic exploration.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, context for 'intermediate knowledge', or how it differs from sibling tools such as 'apresenta', 'compara', 'inicial', 'problemas', or 'revisa'. Without this information, an AI agent must guess based on tool names alone.

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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