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qa-systematic质量保证系统

Agent Skill

qa-systematic 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

912

周安装

38

GitHub Stars

216

下载量

304
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:qa-systematic(质量保证系统)
来源仓库:https://github.com/mathews-tom/armory
仓库路径:skills/qa-systematic
安装命令:
npx skills add https://github.com/mathews-tom/armory --skill qa-systematic
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/mathews-tom/armory --skill qa-systematic

简介

qa-systematic 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合围绕仓库状态、变更或协作事项进行整理。

  • 它支持查询项目动态、分析代码差异或跟踪协作进展。
  • 通过安装命令 npx skills add https://github.com/mathews-tom/armory --skill qa-systematic 添加技能,具体用法可参考仓库中的 SKILL.md。
  • 安装前请确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Systematic QA Testing

Modes

Full (default)

Systematic page-by-page testing, 8-category health score, full issue documentation.

Quick

30-second smoke test of critical paths only: login, main nav, primary action.

Regression

Diff current state against saved baseline, report new/resolved issues.

Browser Automation Detection

Detect available automation in priority order:

  1. Playwright MCP server — check if Playwright tools are available in the current tool list
  2. agent-browser skill — check if the agent-browser skill is loaded
  3. Direct CLI tools — check for playwright, puppeteer, or cypress binaries on PATH
  4. Manual fallback — instruct the user to navigate and report observations

Use the highest-priority method available. State which method is in use at the start of the report.

Workflow

Phase 1: Initialize

  1. Detect mode from user prompt. Default to full if unspecified.
  2. Detect application URL:

- Check references/project-detection.md for framework port conventions (e.g., Next.js → 3000, Vite → 5173, Django → 8000). - If not detectable, ask the user.

  1. Detect available browser automation method (priority list above).
  2. If regression mode: load previous baseline from .qa-reports/.

Phase 2: Authenticate (if needed)

  1. Navigate to root URL and check if a login wall is present.
  2. If credentials were provided: authenticate and store session.
  3. If not: ask the user for test credentials, or skip auth-gated pages and note the gap in the report.

Phase 3: Orient

  1. Navigate to root URL.
  2. Map the primary navigation structure — collect all top-level nav links.
  3. Classify each page: static, form, list, detail, dashboard.
  4. Build a test plan ordered by page category (forms and dashboards first — highest defect density).

Phase 4: Explore (Full mode)

For each page, run the per-page checklist below. In quick mode, run only the items marked with (Q).

Visual Scan

  • (Q) Layout renders correctly — no overlap, no overflow
  • Images load — no broken <img> tags
  • Typography consistent — no visible font fallbacks
  • Responsive: check at desktop (1280px) and mobile (375px) widths

Interactive Elements

  • (Q) All buttons and links are clickable and responsive
  • Hover states present where expected
  • Focus indicators visible for keyboard navigation
  • Disabled states visually distinct

Forms

  • (Q) Required field validation fires on empty submit
  • Error messages display on invalid input
  • Success feedback on valid submission
  • Form resubmission handled — no duplicate submissions on double-click

Navigation

  • (Q) All nav links resolve — no 404s
  • Back button works as expected
  • Deep links work — direct URL access returns correct page
  • Breadcrumbs accurate (if present)

State Management

  • Loading states displayed during async operations
  • Empty states handled — no blank pages when data is absent
  • Error states recoverable — retry or back options present
  • Data persists across navigation — no lost form data on back/forward

Console

  • (Q) No JavaScript errors in console
  • No failed network requests (4xx/5xx)
  • No mixed content warnings
  • No deprecation warnings in hot paths

Responsiveness

  • Mobile layout usable — no horizontal scroll at 375px
  • Touch targets >= 44px
  • Text readable without zoom (>= 16px body text)

Phase 5: Document

For each issue found, classify using references/issue-taxonomy.md:

  • Severity: critical (blocks usage), major (degrades experience), minor (cosmetic/polish)
  • Category: functional, visual, accessibility, performance, content, navigation, security, console
  • Evidence: screenshot description or reproduction steps

Assign a unique ID: QA-001, QA-002, etc.

Compute health score using the weights defined below and detailed in references/report-template.md.

Phase 6: Wrap Up

  1. Generate structured report following references/report-template.md.
  2. Save to .qa-reports/<YYYY-MM-DD>-<mode>.json.
  3. If full mode: save baseline for future regression comparison.
  4. Present summary: health score, critical/major/minor counts, top 3 priority fixes.

Health Score

Weighted average across 8 categories, scored 0-100.

CategoryWeight
Console errors15%
Broken links10%
Functional20%
UX/Usability15%
Accessibility15%
Visual10%
Performance10%
Content5%

Scoring per category: start at 100, deduct per issue by severity:

  • Critical: -30
  • Major: -15
  • Minor: -5

Floor at 0. Final health score = weighted sum of category scores.

Quick Mode Behavior

Run only items marked (Q) in the Phase 4 checklist. Skip health score computation — report pass/fail per critical path. Target completion: 30 seconds of actual testing time.

Regression Mode Behavior

  1. Load the most recent baseline from .qa-reports/.
  2. Run full mode.
  3. Diff issues by ID and description similarity.
  4. Report: new issues, resolved issues, persistent issues.
  5. Save updated baseline.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

34.07%
按下载量换算104

Claude

30.05%
按下载量换算91

Cursor

18.54%
按下载量换算56

Gemini CLI

9.52%
按下载量换算29

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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