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Execute qualquer Skill no Manus com um clique

pytest-optimizer

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Atualizado25 de janeiro de 2026 às 18:01

Analyze and optimize pytest suites to improve speed, identify flaky tests, and increase coverage. Use to maintain high-quality, fast-running test pipelines.

Instalação

Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.

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Fonte

jorgealves

jorgealves/agent_skills

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Ocupações relacionadasSOC

Baseado na classificação ocupacional SOC

Analistas de garantia de qualidade de software e testadoresInformática e Matemática·SOC 15-1253

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SKILL.md

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name	pytest-optimizer
description	Analyze and optimize pytest suites to improve speed, identify flaky tests, and increase coverage. Use to maintain high-quality, fast-running test pipelines.

pytest Optimizer

Purpose and Intent

Analyze and optimize pytest suites to improve speed, identify flaky tests, and increase coverage. Use to maintain high-quality, fast-running test pipelines.

When to Use

Project Setup: When initializing a new Python project.
Continuous Integration: As part of automated build and test pipelines.
Legacy Refactoring: When updating older Python codebases to modern standards.

When NOT to Use

Non-Python Projects: This tool is specialized for the Python ecosystem.

Error Conditions and Edge Cases

Missing Requirements: If the project lacks a requirements.txt or pyproject.toml.
Incompatible Versions: If the project uses a Python version not supported by the tools.

Security and Data-Handling Considerations

All analysis is performed locally.
No source code or credentials are ever transmitted externally.

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name	pytest-optimizer
description	Analyze and optimize pytest suites to improve speed, identify flaky tests, and increase coverage. Use to maintain high-quality, fast-running test pipelines.

pytest Optimizer

Purpose and Intent

Analyze and optimize pytest suites to improve speed, identify flaky tests, and increase coverage. Use to maintain high-quality, fast-running test pipelines.

When to Use

Project Setup: When initializing a new Python project.
Continuous Integration: As part of automated build and test pipelines.
Legacy Refactoring: When updating older Python codebases to modern standards.

When NOT to Use

Non-Python Projects: This tool is specialized for the Python ecosystem.

Error Conditions and Edge Cases

Missing Requirements: If the project lacks a requirements.txt or pyproject.toml.
Incompatible Versions: If the project uses a Python version not supported by the tools.

Security and Data-Handling Considerations

All analysis is performed locally.
No source code or credentials are ever transmitted externally.