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Agent skill

QA Systematic

by Mathews-Tom in Mathews-Tom/armory

Systematic web application QA testing with issue taxonomy, health scoring, and regression tracking.

MITAuto-check passedTesting & QA

Install QA Systematic

skills CLI
$ npx skills add Mathews-Tom/armory --skill qa-systematic -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Mathews-Tom/armory qa-systematic --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Mathews-Tom/armory.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/qa-systematic .claude/skills/qa-systematic && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
qa-systematic
GitHub stars
328
Token cost
~1.4k tokens
SKILL.md length
681 words
Files
5 (incl. references)
Skills in repo
80
Repo updated
First seen
Licence
MIT

At a glance

Systematic web application QA testing with issue taxonomy, health scoring, and regression tracking.

  • Works in 6 steps: Initialize → Authenticate (if needed) → Orient → …
  • Systematic test
  • SKILL.md covers Modes, Browser Automation Detection, Workflow and Health Score, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

QA Systematic is an agent skill from Mathews-Tom/armory. Systematic web application QA testing with issue taxonomy, health scoring, and regression tracking. Triggers on: "QA this", "test the app", "smoke test", "run QA", "systematic test", "regression test", "full QA", "/qa-systematic".

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `evals/cases.yaml`, `references/issue-taxonomy.md` and `references/project-detection.md`).

It sits in Testing & QA, covering QA and bug reports and Browser automation. It works with Playwright. The repository describes itself as: Curated, production-grade skills for AI coding agents. Battle-tested workflows for developers who use AI seriously. The licence is MIT.

When your agent uses it

  • Systematic test
  • Regression test

Example prompts

  • “QA this”
  • “test the app”
  • “smoke test”
  • “/qa-systematic”

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Initialize
  2. Authenticate (if needed)
  3. Orient
  4. Explore (Full mode)
  5. Document
  6. Wrap Up

What it can do on your machine

Read from SKILL.md and the folder at commit 4594fb7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

QA Systematic loads about 1.4k tokens when it runs, and up to ~3.6k if it reads all its reference files. Until then it costs about 61 tokens; SKILL.md has 681 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~61
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Mathews-Tom/armory at commit 4594fb7, republished under its MIT licence (© Mathews-Tom). 681 words, ~1,390 tokens.

Download SKILL.mdSave it as .claude/skills/qa-systematic/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
qa-systematic
description
Systematic web application QA testing with issue taxonomy, health scoring, and regression tracking. Triggers on: "QA this", "test the app", "smoke test", "run QA", "systematic test", "regression test", "full QA", "/qa-systematic".
metadata.version
1.0.1
metadata.category
development
metadata.tags
qa, testing, browser, regression
metadata.difficulty
advanced
metadata.phase
verify

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.
  3. Detect available browser automation method (priority list above).
  4. 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)
Show full SKILL.md (287 more words)Show less
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.

© Mathews-Tom, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (references) in skills/qa-systematic of Mathews-Tom/armory.

  • SKILL.md
  • evals/cases.yaml
  • references/issue-taxonomy.md
  • references/project-detection.md
  • references/report-template.md

Open the folder on GitHubat commit 4594fb7

Compare with similar skills

QA Systematic next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

QA Systematic compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
QA Systematic this skillMathews-Tom/armory328—~1.4kAutomated safety check: PassMIT
Glance TestDebugBase/glance156—~827Automated safety check: PassMIT
Agentic Browser Testingpetrkindlmann/qa-skills165—~4.5kAutomated safety check: PassMIT
Solution Testingkid-sid/claude-spellbook189—~3.9kAutomated safety check: PassMIT
playwright-cli Browser Automationgithub/gh-aw5.4k24 repos~2.8kAutomated safety check: PassMIT
Diagnose Playwright Failure as Product Bugappsmithorg/appsmith41k—~1.5kAutomated safety check: PassApache-2.0

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Works with

Categories

Questions about QA Systematic

What does QA Systematic do?

Systematic web application QA testing with issue taxonomy, health scoring, and regression tracking. QA Systematic is an agent skill from Mathews-Tom/armory. Systematic web application QA testing with issue taxonomy, health scoring, and regression tracking.

When should I use QA Systematic?

QA Systematic fits situations like: systematic test; regression test.

How do I install QA Systematic in Claude Code?

Run `npx skills add Mathews-Tom/armory --skill qa-systematic -a claude-code`. Or copy the skill folder (skills/qa-systematic in Mathews-Tom/armory) into .claude/skills/qa-systematic in your project. Claude Code loads it when a task matches its description.

How do I install QA Systematic in Codex?

Run `npx skills add Mathews-Tom/armory --skill qa-systematic -a codex`. Or copy the skill folder (skills/qa-systematic in Mathews-Tom/armory) into .agents/skills/qa-systematic in your project. Codex loads it when a task matches its description.

Can I use QA Systematic in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Mathews-Tom/armory --skill qa-systematic -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/qa-systematic, .gemini/skills/qa-systematic, .github/skills/qa-systematic and .opencode/skills/qa-systematic in your project.

What does QA Systematic need to run?

SKILL.md names no scripts, command-line tools or credentials: QA Systematic is instructions for the agent only.

Does QA Systematic access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is QA Systematic safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does QA Systematic use?

QA Systematic is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does QA Systematic use?

About 1.4k tokens (SKILL.md is roughly 5.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.3k tokens, read only when the agent opens those files.

What are the alternatives to QA Systematic?

Skills that share tags, products or a category with QA Systematic: Glance Test (DebugBase/glance, 156 stars), Agentic Browser Testing (petrkindlmann/qa-skills, 165 stars), Solution Testing (kid-sid/claude-spellbook, 189 stars) and playwright-cli Browser Automation (github/gh-aw, 5.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains QA Systematic?

Mathews-Tom (a GitHub user) maintains it in Mathews-Tom/armory, which has 328 GitHub stars. The repository holds 80 skills in this directory. The repository was last updated on October 6, 2026.

Source: Mathews-Tom/armory on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.