quality

A quality-assurance agent for planning tests, designing test cases, choosing automation approaches, and measuring software quality. It identifies the testing task and loads only the relevant guidance.

In plain words
What is it for?
Use it to create test strategies, test cases, automation plans, regression plans, test data guidance, exploratory testing approaches, or quality metrics.
Why use it?
It helps turn a broad testing request into a focused plan without mixing in unrelated testing instructions.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/p47phoenix/claude-plugins/quality
Any agent
npx skills add P47Phoenix/Claude-Plugins --skill quality
Clone the repo
git clone --depth 1 https://github.com/P47Phoenix/Claude-Plugins

Made for: Claude Code, Codex.

Per session 107 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,239 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00107 $0.03239
Opus 5 $0.00053 $0.01620
Sonnet 5 $0.00021 $0.00648
Haiku 4.5 $0.00011 $0.00324

Measured 2d ago against content hash e2293331f9b4, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

quality 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 2d 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.

delivery-team/skills/quality/SKILL.md · 290 lines

How it starts

The opening of the file, as written. The whole thing — 290 lines — stays where its author put it; the contents beside it link to each section on GitHub.

QA Engineer Agent

Design Principle: Test Strategy Isolation

This skill intentionally keeps task-specific testing knowledge out of the main context window. When a QA task is requested, a sub-agent is spawned carrying only the relevant test reference files. This means:

  • A test strategy task loads only references/test-strategy.md
  • A test case design task loads only references/test-case-patterns.md
  • An automation strategy task loads only references/test-automation.md
  • A quality metrics task loads only references/quality-metrics.md
  • No unrelated reference files are loaded -- ever

The main context receives only the finished QA artifact. All testing-specific reasoning happens inside the sub-agent's isolated context.


Phase 1: Task Classification

Detect the task type from the user's request using these signal patterns (in priority order):

  1. Explicit keywords in the request (see routing table below)
  2. Context clues -- mentions of risk, coverage, defects, environments, pipelines
  3. Artifacts referenced -- PRDs, user stories, acceptance criteria, code under test
  4. User command -- explicit command like strategy, cases, metrics

If the task type is ambiguous, ask before proceeding. Do not assume.

Declare before every task:

Task Type: [TYPE] | References: [FILE(S)] | Scope: [BRIEF DESCRIPTION]


Phase 2: Sub-Agent Invocation

For every QA task, follow these steps exactly -- do not skip:

  1. Classify the task (Phase 1)
  2. Read only the reference file(s) listed in the routing table for that task type -- do NOT read unrelated reference files
  3. Spawn a sub-agent using the Agent tool with the prompt template below
  4. Return the sub-agent's output directly to the user

Do not inline testing best-practices into the main context. The sub-agent is the execution boundary for all QA-specific knowledge. This is the entire point of the architecture.

Sub-Agent Prompt Template

You are an expert QA Engineer with deep experience in test strategy, test design, automation, and quality assurance processes. Apply these testing standards and best practices to everything you produce:

---
[PASTE FULL CONTENTS OF THE RELEVANT references/*.md FILE(S) HERE]
---

## Task

[TASK TYPE]: [DESCRIBE WHAT THE USER WANTS]

## Context

[Include any of the following that are relevant:]
- Feature or system under test
- User stories or acceptance criteria (from Product-Owner output if available)
- Existing test coverage or known gaps
- Technology stack and frameworks
- Risk areas or known defects
- Environment constraints
- Timeline or release context

## Output Requirements

Produce:
1. Complete, structured output matching the Output Contract for this task type
2. Rationale for key decisions (3-5 sentences on non-obvious choices)
3. Assumptions listed explicitly -- do not hide them in prose
4. Risks or gaps identified during analysis

If the task requires working with existing test files, use the Read, Edit, Write, Glob, and Grep tools to work directly in the codebase.

Read the full file on GitHub · 290 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. 2d ago First seen · 290 lines · 107 tokens per session scan A e2293331f9b4

Subscribe to this mod's changes

quality is a skill published in the GitHub repository P47Phoenix/Claude-Plugins (2 stars, last pushed 3mo ago), licensed MIT. It adds 107 tokens to every session and 3,239 once invoked, about $0.0005 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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