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    QA SDET-ISTQB

    1

    Turns any AI coding agent into a senior ISTQB-certified SDET — risk-based test strategy, structured test design, and multi-framework automation (Playwright, Selenium, Cypress, Appium, Robot Framework) in one skill.

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    QA SDET-ISTQB

    QA SDET-ISTQB

    Example session with this skill installed

    We're shipping a new "subscription checkout" flow next sprint — card payment via Stripe, plus a
GraphQL API for managing subscription plans. I need:

1. A risk analysis of this feature before we scope testing.
2. A full test strategy and a structured set of test cases (happy path, unhappy path, and edge
   cases) for both the checkout UI and the subscriptions API.
3. Playwright + TypeScript automation (Page Object Model) for the critical checkout UI flows.
4. API test automation for the GraphQL subscriptions endpoints — status codes, schema validation,
   and idempotency on retries.
5. Tell me what should go in our smoke suite vs. full regression, and generate a GitHub Actions
   pipeline that runs smoke on every PR and full regression nightly.

We're on Node 20, TypeScript, and our product repo is `apps/checkout`. Put any test code in a
separate `qa/` repo — don't touch the product code.
    • Read your context and instructions
    • Compiled the qa sdet-istqb
    
## Risk Analysis: Subscription Checkout + Plans API

| Factor | Score (1-5) | Weight | Weighted |
|---|---|---|---|
| Business impact | 5 | 30% | 1.50 |
| Technical complexity | 4 | 25% | 1.00 |
| Change frequency | 3 | 20% | 0.60 |
| Test coverage gap | 5 | 15% | 0.75 |
| Dependency risk | 4 | 10% | 0.40 |
| **Total** | | | **4.25 — 🔴 HIGH** |


Thorough testing required: this touches payments and a third-party dependency (Stripe) with zero
existing coverage. Blocking merge without integration + contract tests is justified.

## Test Strategy (summary)
- **Scope:** checkout UI (card payment) + subscriptions GraphQL API (create/update/cancel plan)
- **Levels:** component (page objects), integration (API ↔ Stripe sandbox), system (full checkout flow)
- **Techniques:** equivalence partitioning + boundary value analysis on card/amount fields, decision tables for plan upgrade/downgrade rules
- **Exit criteria:** 0 open P1/P2 defects, smoke suite green, idempotency verified on 3 consecutive retries

## Test Cases (excerpt — 34 generated, full set delivered as markdown + CSV)

| ID | Title | Type | Priority |
|---|---|---|---|
| TC-001 | Valid card completes checkout and activates plan | Happy | P1 |
| TC-014 | Declined card shows specific decline reason, no plan activated | Unhappy | P1 |
| TC-019 | Retry with same idempotency key does not double-charge | Corner | P1 |
| TC-027 | Cancel plan mid-billing-cycle prorates correctly | Unhappy | P2 |
| TC-033 | GraphQL mutation with missing required field returns typed error, not 500 | Unhappy | P1 |


## Automation delivered

\`\`\`
qa/
├── tests/pages/CheckoutPage.ts        # Page Object — Playwright + TS
├── tests/specs/checkout.spec.ts       # 11 UI scenarios (happy/unhappy/corner)
├── tests/api/subscriptions.spec.ts    # 14 GraphQL scenarios incl. idempotency retry
├── .github/workflows/qa-pipeline.yml  # smoke on PR, full regression nightly
\`\`\`

## Coverage analysis
- Happy path: 9 tests (26%)
- Unhappy path: 16 tests (47%) — includes every documented Stripe decline code
- Corner cases: 9 tests (27%) — concurrency on double-submit, idempotency retries, boundary amounts ($0.01, max charge)
- **Gaps (explicit):** 3-D Secure challenge flow not covered — no sandbox test card provided; flagged for a follow-up pass.

## Next steps
1. Review the 3 P1 corner cases (idempotency, decline handling, GraphQL validation) before merge — these currently drive the HIGH risk score.
2. Drop `qa/` into its own repo per the test-repo handoff convention; nothing touches `apps/checkout`.
3. Confirm the CI pipeline's nightly schedule against your existing Actions quota.
4. Share Stripe 3-D Secure test cases so the flagged coverage gap can be closed next pass.

*(Abridged for this listing — the actual response delivers complete, runnable file contents for
every automation file, the full 34-case test suite, and the full pipeline YAML.)*

    Connects securely to your tools. The creator never sees your data.

    About this skill

    SDET-ISTQB turns your AI coding agent into a senior Software Development Engineer in Test (SDET) who works the way ISTQB-certified quality engineers do not a generic "write some tests" assistant, but a complete software quality assurance system built on ISTQB standards (Foundation v4.0 + Advanced Core), modern industry best practices, and real SDET workflow discipline, covering every core aspect of QA engineering end to end.

    Instead of improvising ad hoc test ideas, your agent follows the same structured workflow a senior SDET would: understand context → analyze risk → define strategy → design cases → classify for CI → automate what's worth automating → wire into the pipeline → learn the project's conventions and never skips the unhappy-path or edge-case coverage that ad hoc testing tends to miss.

    Why it pays for itself: untested edge cases and bugs that reach production are some of the most expensive failures in software delivery in rework, incident response, and lost trust. A single missed unhappy-path or boundary case in production can cost a team far more than this skill does. By forcing explicit happy/unhappy/corner-case coverage, risk-weighted prioritization, and ISTQB-grade rigor on every deliverable, this skill helps teams catch what they'd otherwise miss before it ships cutting defect-escape costs, rushed hotfixes, and the hours spent re-litigating "did we test this?" after the fact. It's a QA engineer's judgment, on demand, for a fraction of the cost.

    It ships as a self-contained Agent Skill package (SKILL.md + on-demand reference modules), so your agent loads only a ~4K-token entry point by default and pulls in deeper knowledge (a specific framework, language, or testing domain) only when the task actually needs it no context bloat, no irrelevant noise in the response.

    What's inside

    Core QA engineering

    • ISTQB terminology, test levels, test types, black-box/white-box/experience-based techniques, estimation methods, and defect management (Foundation v4.0 + Advanced Core)
    • Test strategy & test plan generation
    • Structured test case design (TC-XXX format, happy/unhappy/corner-case coverage, traceability)
    • Risk-based analysis with a weighted scoring matrix for features and user stories
    • Merge/pull request impact analysis what a code change puts at risk and what to re-test
    • Test suite classification into S/M/L/XL tiers for CI/CD integration
    • Exploratory testing with session-based test management (charters, heuristics, SBTM)
    • Industry best practices: test pyramid shape, shift-left testing, flaky-test triage, test data strategy, contract testing, feature flags, release criteria

    Non-functional & specialized testing

    • API testing (REST/GraphQL): contract/schema validation, status codes, idempotency, pagination, auth, side-effect verification
    • Accessibility testing: WCAG criteria by level, what's automatable vs. manual, keyboard navigation, screen readers
    • Performance testing: load/stress/soak types, percentile-based goals, realistic load design
    • Security testing: OWASP Top 10 applied to test cases, access control, input validation, secrets handling, SAST/DAST/SCA

    Automation multi-framework, multi-language

    • Playwright + TypeScript with Page Object Model
    • Cypress (JavaScript/TypeScript)
    • Selenium WebDriver (Java and Python)
    • Appium for mobile (iOS/Android)
    • Robot Framework (keyword-driven web, API, desktop)
    • Language-specific patterns for Python (pytest), Java (JUnit 5/TestNG), JavaScript/TypeScript (Jest/Vitest)
    • Gherkin/BDD and Cucumber step definitions
    • Maven/Gradle build and dependency patterns
    • CI/CD pipeline generation for GitHub Actions, GitLab CI, and Jenkins

    Operating model

    • Independent test-repository structure, separated from the product codebase, with a defined handoff format for proposals to the development team
    • Read-only boundary on the product under test, with an explicit 6-step defect protocol (report → confirm → review own coverage gap → propose/write the missing test → update suites by severity → never patch the product)
    • Project-specific pattern memory, so the agent stops re-asking what it already learned about your codebase

    Built for teams who want their AI agent to behave like a disciplined, senior-level quality engineer by default not one that has to be re-taught ISTQB fundamentals and test design discipline in every new conversation.

    How to use

    Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

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    Requires

    test design, ISTQB knowledge) this runs purely on the model reading `SKILL.md`/`references/`.
    run the included install/validate scripts)
    test-artifacts/test-repo location
    specific automation stack you ask the agent to generate/run
    framework's own installer) if you want the agent to actually execute UI tests, not just
    generate them
    project-pattern-recall module (degrades gracefully if unavailable)
    Python
    playwright
    Node.js
    Git

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    What's inside

    Frequently Asked Questions