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sigaa_main_data

Get core academic data after login, including student name, enrollment, summarized semester classes, academic indices, and pending workload.

Instructions

Ponto de entrada depois do login: nome, matrícula, turmas do semestre (resumidas, sem cronograma/notícia/faltas — use sigaa_get_turma para detalhar cada uma), índices acadêmicos e carga horária pendente.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations and no output schema, the description carries the behavioral burden and does well: it discloses the login prerequisite, the summarized nature of the data, and what is omitted. It stops short of stating read-only behavior or error conditions when not logged in, but those are reasonably inferable from 'depois do login'.

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 definition is a single dense sentence that front-loads the most important context ('Ponto de entrada depois do login') and organizes the rest with parentheses and a dash. Every phrase adds information and there is no redundancy or 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?

For a no-argument data-retrieval tool, this is largely complete: it names the main data categories and points to the relevant sibling for deeper detail. However, since there is no output schema, the description only gives high-level categories and not the exact response structure, which is a modest gap for an agent that must interpret the return value.

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 the baseline is 4; there are no parameter semantics to document. The description adds nothing about parameters because nothing is needed.

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 identifies the tool as the post-login entry point and enumerates the data it provides: nome, matrícula, turmas resumidas, índices acadêmicos e carga horária pendente. It also distinguishes itself from sigaa_get_turma by explicitly stating that turmas are summarized and that the sibling tool should be used for details.

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

Usage Guidelines5/5

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

It states when to use the tool ('depois do login') and gives an explicit alternative: use sigaa_get_turma when detailed class information is needed. The exclusion of cronograma/notícia/faltas further tells an agent which scenarios this tool is NOT appropriate for.

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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