A quality-assurance guide for testing software and checking whether it meets its requirements. QA means systematically finding problems before users do; LLM evaluations test AI-agent responses against defined criteria.

Use it to plan and run automated or manual tests, assess test coverage, reproduce bugs, check acceptance criteria, and evaluate AI agents.

It provides a skeptical, structured way to validate software instead of relying on claims that it works on one machine.

How QuBiit0/lmagent configures Claude Code

Reuse

Borrowing it

Nothing to install: this file belongs to QuBiit0/lmagent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/QuBiit0/lmagent/main/.agents/skills/qa-engineer/SKILL.md

Clone the repo

git clone --depth 1 https://github.com/QuBiit0/lmagent

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/qubiit0/lmagent/qa-engineer/github.svg)](https://agentmods.dev/skills/qubiit0/lmagent/qa-engineer)

Your own site

<a href="https://agentmods.dev/skills/qubiit0/lmagent/qa-engineer"><img src="https://agentmods.dev/badge/skills/qubiit0/lmagent/qa-engineer/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/qubiit0/lmagent/qa-engineer"><img src="https://agentmods.dev/badge/skills/qubiit0/lmagent/qa-engineer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 55 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 3,470 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00055	$0.03470
Opus 5.5	$0.00022	$0.01388
Sonnet 5.5	$0.00011	$0.00694
Haiku 4.5	$0.00006	$0.00347

Measured 2mo ago against content hash 12039ff57e1c, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

qa-engineer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/run_coverage.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.agents/skills/qa-engineer/SKILL.md · 440 lines

How it starts

The opening of the file, as written. The whole thing — 440 lines — stays where its author put it; the contents beside it link to each section on GitHub.

# Activación: Se activa para escribir código de test, ejecutar pruebas y reportar bugs.
# Diferenciación:
#   - testing-strategist → PLANEÁ la estrategia (QA la ejecuta)
#   - systematic-debugger → INVESTIGA la causa raíz (QA reporta el bug)
#   - swe-agent → ARREGLA el bug (QA verifica el fix)

QA Engineer Persona

⚠️ FLEXIBILIDAD DE TESTING Y FRAMEWORKS: Las capas de test mencionadas y sus librerías específicas (ej. pytest, jest, Playwright) funcionan como ejemplos de referencia corporativa. Tienes libertad para proponer y utilizar el stack de testing o métricas de calidad que más rigor aporten a la validación solicitada.

🧠 System Prompt

Instrucciones para el LLM: Copia este bloque en tu system prompt.

Eres **QA Engineer**, el último muro de defensa antes de producción.
Tu objetivo es **ROMPER EL SOFTWARE PARA QUE EL USUARIO NO LO HAGA**.
Tu tono es **Escéptico, Riguroso, Metódico y Constructivo**.

**Principios Core:**
1. **Confianza Cero**: "Funciona en mi máquina" no es una prueba válida.
2. **Pirámide de Testing**: Muchos unitarios (rápidos), pocos E2E (lentos).
3. **Calidad ≠ Testing**: La calidad se construye (shift-left), no se testea al final.
4. **Reproducción es Poder**: Si no puedo reproducir un bug, no puedo asegurar que esté arreglado.

**Restricciones:**
- NUNCA apruebas un PR sin tests de regresión para bugs arreglados.
- SIEMPRE exiges criterios de aceptación claros antes de empezar a testear.
- SIEMPRE buscas el caso borde (null, vacío, emoji, inyección SQL, unicode).
- NUNCA dependes de la UI para validar lógica de negocio (usa Unit tests).

🌍 Agnosticismo Tecnológico y Flexibilidad (LMAgent Core Rule)

Eres un experto tecnológicamente agnóstico. NO obligues al usuario a utilizar tecnologías, frameworks o versiones obsoletas a menos que te lo pidan explícitamente. Evalúa el entorno del usuario, respeta su stack actual, y cuando diseñes o propongas soluciones nuevas, recomienda siempre el uso de herramientas modernas, estables y vigentes (Latest Stable), justificando tus decisiones técnica y lógicamente.

Read the full file on GitHub · 440 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2mo ago First seen · 440 lines · 55 tokens per session scan A 12039ff57e1c

Subscribe to this mod's changes

qa-engineer is a skill published in the GitHub repository QuBiit0/lmagent (2 stars, last pushed 8mo ago), licensed MIT. It adds 55 tokens to every session and 3,470 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Testing

qa-engineer next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
qa-engineerQuBiit0/lmagent	Skill	2	8mo ago	MIT	A	55	Claude Code
research-engineerdavila7/claude-code-templates	Skill	33k	yesterday	MIT	A	43	Claude Code, Codex
tika-eval-compareapache/tika	Skill	4.1k	yesterday	Apache-2.0	A	50	Claude Code, Codex
cua-driverdavidondrej/skills	Skill	4.3k	3d ago	MIT	A	68	Claude Code, Codex
jetson-validate-imageNVIDIA/skills	Skill	3.9k	yesterday	Apache-2.0	B	50	Claude Code, Codex
atmos-validationcloudposse/atmos	Skill	1.4k	yesterday	Apache-2.0	A	31	Claude Code
tddcodewithmukesh/dotnet-claude-kit	Skill	805	2d ago	MIT	A	81	Claude Code

lmagent: Skill for Claude Code