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QA Suite Architect

QA Suite Architect

Turns a user story or ticket into a verified, minimal test suite. Derives every case from a formal technique (boundary value analysis, equivalence partitioning, decision tables), reduces configuration combinations pairwise, and runs a deterministic script to prove coverage instead of just listing cases. Includes a security pass built from real OWASP findings and Playwright export.
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如何使用
在 Capafy 上运行
也可用于外部应用
创作者提供
Claude Sonnet 5

What this does

Most test-case generators give you a longer list. This one gives you a shorter suite that's proven complete.

Paste a user story or ticket. You get back a full test suite — functional, negative, boundary, security, and accessibility cases — built from formal test design techniques, verified by deterministic scripts, not just generated and hoped for.

Why it's different

It lints your spec before writing a single test. "The system should respond quickly" produces a test that passes no matter what the system does. This agent catches vague acceptance criteria first and tells you exactly what to clarify — before any test gets written.

Every case is derived, not guessed. Boundary value analysis, equivalence partitioning, decision tables, state transition testing — including the invalid transitions almost nobody thinks to test. Each case names the technique that produced it, so you can check the reasoning instead of just trusting it.

Combinations get reduced with real math. Testing across 4 browsers × 3 roles × 3 plans × 2 locales? That's 72 combinations. Pairwise reduction covers every pair in about 12 cases — a script proves it, not an estimate.

Coverage is verified, not asserted. A deterministic check reports exactly which acceptance criterion has no test behind it, which case traces to nothing, and which case skipped its technique. You get the passing report alongside the suite.

Security cases come from real findings, not a generic checklist. Account enumeration via response timing. IDOR by ID substitution. Stored XSS that shows up in the CSV export, not the login form. CSV formula injection. Race conditions on the last item in stock.

Example input → output

You send:

PROJ-1234 — Email/password sign-in

As a returning user I want to sign in with email and password
so I can reach my dashboard.

Acceptance criteria:
- Valid credentials land the user on /dashboard
- Invalid credentials show one generic error message
- The account locks for 15 minutes after 5 failed attempts

You get back:

  • A spec-quality check flagging anything ambiguous ("shows an error" → which error, exactly?)
  • 12–15 test cases covering the happy path, every boundary on the lockout counter, the enumeration risk on the error message, session and browser-back edge cases, and the invalid state transitions (submitting while already locked, resetting mid-lockout)
  • Each case tagged with its derivation: BVA — upper boundary, exactly on, Checklist — OWASP account enumeration, etc.
  • A verification report: 100% of acceptance criteria covered, 0 orphan cases, 0 cases missing a technique
  • Playwright test specs on request, or export formats for TestRail, Xray, Zephyr, and Qase

Who this is for

  • Developers who own their own testing and don't have a dedicated QA engineer
  • The one QA person on a team who needs to move faster without cutting corners
  • Anyone who has to defend a test plan in a review or prove coverage for an audit
  • Teams tired of test suites that look thorough but quietly skip the case that ships the bug

FAQ

Does it replace a QA engineer?
No. It replaces the blank page and the "did I forget something?" doubt. You still decide what matters for your product — this makes sure the mechanical coverage work is actually complete.

What if my acceptance criteria are rough or incomplete?
That's fine — the agent extracts and drafts criteria from a plain description if none are given, then lints them for you to confirm before generating anything.

Can I get Playwright tests directly?
Yes — ask for Playwright specs and it emits role-based, locator-safe test skeletons ready to fill in.

What test design techniques does it actually use?
Equivalence partitioning, boundary value analysis, decision tables, state transition testing (including invalid transitions), and pairwise combination reduction — the same techniques covered in ISTQB foundation-level testing.

Does it work for APIs, not just UI flows?
Yes. Paste an API contract or endpoint description instead of a UI story — the same technique selection and verification process applies.