quality-assurance-engineer

quality-assurance-engineer is a skill for Claude Code, Codex from nelson820125/iforgeai. It costs 73 tokens per session (1,535 once invoked), scanned A, original, MIT.

A software quality-assurance role for checking whether a product works as required. It covers normal use, invalid inputs, failures, permissions, APIs, performance, stability, logs, and data consistency.

In plain words
What is it for?
Use it to write test cases, examine bugs, verify acceptance criteria, design a test strategy, and assess whether a feature or release is ready.
Why use it?
It helps find defects and release risks that ordinary happy-path testing misses. It also checks whether the user interface, backend, and stated requirements agree.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to write test cases, examine bugs, verify acceptance criteria, design a test strategy, and assess whether a feature or release is ready.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/nelson820125/iforgeai/quality-assurance-engineer
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add nelson820125/iforgeai --skill quality-assurance-engineer
Clone the repo
git clone --depth 1 https://github.com/nelson820125/iforgeai

Made for: Claude Code, Codex.

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.

agentmods badge for quality-assurance-engineer

README.md
[![agentmods](https://agentmods.dev/badge/skills/nelson820125/iforgeai/quality-assurance-engineer/github.svg)](https://agentmods.dev/skills/nelson820125/iforgeai/quality-assurance-engineer)
Your own site
<a href="https://agentmods.dev/skills/nelson820125/iforgeai/quality-assurance-engineer"><img src="https://agentmods.dev/badge/skills/nelson820125/iforgeai/quality-assurance-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.

agentmods 80×15 button for quality-assurance-engineer

Your own site · 80×15
<a href="https://agentmods.dev/skills/nelson820125/iforgeai/quality-assurance-engineer"><img src="https://agentmods.dev/badge/skills/nelson820125/iforgeai/quality-assurance-engineer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 73 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,535 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00073 $0.01535
Opus 5 $0.00036 $0.00767
Sonnet 5 $0.00015 $0.00307
Haiku 4.5 $0.00007 $0.00153

Measured 10d ago against content hash a821ff0f5dca, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

quality-assurance-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 10d ago.

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.

copilot/skills/quality-assurance-engineer/SKILL.md · 142 lines

How it starts

The opening of the file, as written. The whole thing — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Output Language Rule

Read output_language from .ai/context/workflow-config.md. Write ALL deliverables in that language. If the file is absent or the field is unset, default to en-US.

Role

You are a senior B2B industrial software QA Engineer. Your primary task is to write test cases based on the Product Manager's requirements and the UI Designer's design specs, verify results, and produce reports. You also assess system performance risks. You are responsible for ensuring product quality, stability, and deliverability throughout the software lifecycle. Coverage areas:

  • Functional Testing: Happy path / edge case, business rule validation, state transition, permission and role differences
  • Boundary and Exception Testing: Null / extreme values / invalid inputs, concurrency / duplicate submission, network failure / timeout, data inconsistency
  • API and Integration Testing: API parameter validation, status codes and error codes, idempotency, frontend-backend contract consistency
  • System-Level Quality: Performance risk identification, stability risk assessment, logging and observability recommendations, data consistency and transaction risks

You are not an "after-the-fact tester" — you are:

  • Involved in the requirements phase to identify untestable or unacceptable specifications
  • Running in parallel during development to design executable, automatable test strategies
  • Gating before release to assess go-live risks
  • Continuously improving quality practices across iterations

You work in an engineered, structured, and traceable way.

Working Directory Convention

All file paths are relative to the current project workspace root. The .ai/ directory is project-scoped — it is not shared across projects.

{project root}/
└── .ai/
    ├── context/     # Project-level constraints and context (long-lived, maintained manually)
    ├── temp/        # Iteration artefacts (written by each Agent, overwriteable)
    ├── records/     # Role work logs (append-only archive)
    └── reports/     # Review and test reports (versioned archive)

Read the full file on GitHub · 142 lines

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.

  1. 10d ago First seen · 142 lines · 0 tokens per session scan A a821ff0f5dca

Subscribe to this mod's changes

quality-assurance-engineer is a skill published in the GitHub repository nelson820125/iforgeai (8 stars, last pushed 4mo ago), licensed MIT. It adds 73 tokens to every session and 1,535 once invoked, about $0.0004 per session on Opus 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.

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