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Generate Academic Resumo

generate_academic_resumo

Generates NBR 6028:2021-compliant academic abstracts in Portuguese or English from structured research inputs, formatting keywords and validating word counts.

Instructions

Gera um Resumo (em português) ou Abstract (em inglês) na estrutura canônica da NBR 6028:2021:

  • Parágrafo único contínuo.

  • Verbos na 3ª pessoa e linguagem impessoal concisa.

  • Avalia a faixa de palavras (150 a 500 para TCC/teses).

  • Formata palavras-chave separadas por ponto e vírgula e terminadas em ponto.

Input Schema

NameRequiredDescriptionDefault
contextYes
resultsYes
keywordsYes
languageNopt
objectiveYes
conclusionYes
methodologyYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does disclose the enforceable output rules (single paragraph, 3rd person, 150–500 words, keyword punctuation) and hints at a word-range evaluation step, which is useful. It never says whether this is a pure read/generation operation or writes a file, nor what happens when the input falls outside the 150–500 range, so mutation/error behavior remains unclear.

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?

The purpose sentence is front-loaded and the four bullet points are terse and each carries a distinct constraint. No filler or repetition, though the bullets describe output format rather than the missing input guidance.

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?

An output schema exists, so return values need not be explained, and the formatting rules are thorough. However, with six required, undescribed parameters and no annotations, the definition leaves the agent guessing about what content each input should contain and how strictly the word range is enforced — a real gap for a 7-parameter tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% across 7 parameters, so the description must compensate and largely does not. It covers only `language` (pt vs en) and `keywords` (semicolon-separated, period-terminated), leaving context, objective, methodology, results, and conclusion — five of six required inputs — completely undocumented in both schema and description.

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 artifact: generates a Resumo/Abstract following NBR 6028:2021, with the format rules enumerated. It is clearly distinguishable from any sibling (none of the others produce abstracts), though it never names a sibling or explicitly says 'this is not a citation/formatter tool'.

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 only implied — an agent can infer it is the tool for producing an abstract from drafted research content. There is no explicit 'use when' statement, no mention of prerequisites (e.g. content must already exist), and no exclusions or alternatives among the many academic siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.