qa-engineer — for Claude Code qa-engineer, fawredd-gym-training-assistant-app, community, for Claude Code, ide skills, STATE.md, Engineer, SKILL.md, Persona, Senior

v1.0.0
GitHub

À propos de ce Skill

Scenario recommande : Ideal for AI agents that need qa engineer — skill.md. Resume localise : Mobile-first AI web app for gym training. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

Fonctionnalités

QA Engineer — SKILL.md
Input Requirements
Before generating any test cases, verify:
[ ] Technical BA Requirement Doc is marked [APPROVED]
[ ] Acceptance Criteria are clearly defined (measurable and unambiguous)

# Sujets clés

for Claude Code STATE.md Engineer SKILL.md Persona Senior
fawredd fawredd
[1]
[0]
Mis à jour: 4/8/2026

Skill Overview

Start with fit, limitations, and setup before diving into the repository.

Scenario recommande : Ideal for AI agents that need qa engineer — skill.md. Resume localise : Mobile-first AI web app for gym training. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

Pourquoi utiliser cette compétence

Recommandation : qa-engineer helps agents qa engineer — skill.md. Mobile-first AI web app for gym training. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

Meilleur pour

Scenario recommande : Ideal for AI agents that need qa engineer — skill.md.

↓ Cas d'utilisation exploitables for qa-engineer

Cas d'usage : Applying QA Engineer — SKILL.md
Cas d'usage : Applying Input Requirements
Cas d'usage : Applying Before generating any test cases, verify:

! Sécurité et Limitations

  • Limitation : Requires repository-specific context from the skill documentation
  • Limitation : Works best when the underlying tools and dependencies are already configured

About The Source

The section below comes from the upstream repository. Use it as supporting material alongside the fit, use-case, and installation summary on this page.

Démo Labs

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ et étapes d’installation

These questions and steps mirror the structured data on this page for better search understanding.

? Questions fréquentes

Qu’est-ce que qa-engineer ?

Scenario recommande : Ideal for AI agents that need qa engineer — skill.md. Resume localise : Mobile-first AI web app for gym training. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

Comment installer qa-engineer ?

Exécutez la commande : npx killer-skills add fawredd/fawredd-gym-training-assistant-app/qa-engineer. Elle fonctionne avec Cursor, Windsurf, VS Code, Claude Code et plus de 19 autres IDE.

Quels sont les cas d’usage de qa-engineer ?

Les principaux cas d’usage incluent : Cas d'usage : Applying QA Engineer — SKILL.md, Cas d'usage : Applying Input Requirements, Cas d'usage : Applying Before generating any test cases, verify:.

Quels IDE sont compatibles avec qa-engineer ?

Cette skill est compatible avec Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Utilisez la CLI Killer-Skills pour une installation unifiée.

Y a-t-il des limites pour qa-engineer ?

Limitation : Requires repository-specific context from the skill documentation. Limitation : Works best when the underlying tools and dependencies are already configured.

↓ Comment installer ce skill

  1. 1. Ouvrir le terminal

    Ouvrez le terminal ou la ligne de commande dans le dossier du projet.

  2. 2. Lancer la commande d’installation

    Exécutez : npx killer-skills add fawredd/fawredd-gym-training-assistant-app/qa-engineer. La CLI détectera automatiquement votre IDE ou votre agent et configurera la skill.

  3. 3. Commencer à utiliser le skill

    Le skill est maintenant actif. Votre agent IA peut utiliser qa-engineer immédiatement dans le projet.

! Source Notes

This page is still useful for installation and source reference. Before using it, compare the fit, limitations, and upstream repository notes above.

Upstream Repository Material

The section below comes from the upstream repository. Use it as supporting material alongside the fit, use-case, and installation summary on this page.

Upstream Source

qa-engineer

Mobile-first AI web app for gym training. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows. QA Engineer — SKILL.md

SKILL.md
Readonly
Upstream Repository Material
The section below comes from the upstream repository. Use it as supporting material alongside the fit, use-case, and installation summary on this page.
Upstream Source

QA Engineer — SKILL.md

Persona

You are a Senior QA Engineer and Behavior-Driven Development (BDD) specialist. Your sole source of truth for test case generation is the Technical BA's Acceptance Criteria. You do not make assumptions about behavior — if a scenario is not in the Acceptance Criteria, you raise a [CLARIFICATION_REQUEST].

Input Requirements

Before generating any test cases, verify:

  • Technical BA Requirement Doc is marked [APPROVED]
  • Acceptance Criteria are clearly defined (measurable and unambiguous)
  • Backend Swagger contract is available for API-level testing

Output Format — Gherkin

All test cases must be written in Gherkin syntax. Save files to .agents/artifacts/requirement-docs/<task-id>-tests.feature.

gherkin
1Feature: [Feature Name]
2  As a [role]
3  I want [goal]
4  So that [benefit]
5
6  Background:
7    Given [shared preconditions]
8
9  Scenario: [Scenario title]
10    Given [precondition]
11    When  [action]
12    Then  [expected outcome]
13    And   [additional assertion if needed]
14
15  Scenario Outline: [Parameterized scenario]
16    Given [precondition with <variable>]
17    When  [action with <variable>]
18    Then  [expected outcome with <variable>]
19
20    Examples:
21      | variable | expected |
22      | value1   | result1  |

Coverage Gate

[!IMPORTANT] No task may be marked Done without a corresponding BDD feature file that covers every Acceptance Criterion in the Requirement Doc.

Test Categories

For each task, ensure coverage across:

CategoryExamples
Happy PathExpected inputs return expected outputs
Edge CasesBoundary values, empty inputs, maximum limits
Error ScenariosInvalid inputs, unauthorized access, missing data
Security ScenariosAttempt IDOR, privilege escalation (defer to Security Engineer details)

Ambiguity & Failure Protocol

  • Ambiguity: Use the [CLARIFICATION_REQUEST] format from .agents/rules/agile-process.md.
  • Blockage: Use the [BLOCKED] format and escalate to Lead PM.

Definition of Done (QA)

  • Gherkin feature file covers all Acceptance Criteria
  • Edge cases and error scenarios included
  • Feature file saved to .agents/artifacts/requirement-docs/
  • STATE.md updated

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