Magnus HedemarkandGitHub
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Engineering: backend-engineering, frontend-engineering, data-engineering, ml-engineering, platform-engineering, qa-methodology Executive: go-to-market, legal-strategy, operational-design, org-design, product-strategy ml-engineering: added missing training-infrastructure.md reference qa-methodology: added test-data-management, performance-testing, security-testing references All frontmatter converted to agent-skills convention. Source: https://github.com/magnus919/hermes-profiles
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name, description, license, metadata
| name | description | license | metadata | ||||
|---|---|---|---|---|---|---|---|
| qa-methodology | Quality assurance methodology — test strategy design, test automation patterns, regression testing, CI quality gates, test data management, and quality metrics. Grounded in practical patterns for teams that want confident shipping. | MIT |
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QA Methodology
Quality assurance is the practice of making confident shipping routine. This methodology covers test strategy, automation, regression management, and quality metrics that scale with a project's complexity.
The QA Engineer's Domain
| You own | You don't own |
|---|---|
| Test strategy — what to test, at what level, with what priority | Code review — that's the reviewer |
| Test automation — framework selection, test harness setup, CI integration | Root cause analysis of bugs — that's the debugger |
| Regression testing — suites that catch regressions without becoming brittle | Feature implementation — that's the developer |
| Quality gates — CI integration, pass/fail criteria, blocking vs non-blocking | Kanban workflow design — that's the kanban strategist |
| Test data management — fixtures, factories, synthetic data | Production monitoring — that's SRE |
| Quality metrics — coverage analysis, defect density, MTD | Verdict on completion — that's the verifier |
Reference Files
| Reference | When to load |
|---|---|
references/test-strategy.md |
Designing a test strategy for a new project or feature — test levels, risk analysis, prioritization, automation targets |
references/test-automation-gates-metrics.md |
Test automation framework selection, CI integration (parallel execution, sharding, flaky management), quality gate design (pass/fail criteria, blocking vs advisory, evolution), and quality metrics (coverage, defect density, MTTD/MTTR) |
references/regression-testing.md |
Building and maintaining regression suites — selection criteria, prioritization, suite evolution, false positive management |
references/test-data-management.md |
Test data strategy — fixtures vs factories, isolation, synthetic data, PII rules, external service mocking, volume testing |
references/performance-testing.md |
Performance testing — load/stress/soak/spike types, k6 patterns, metrics interpretation, CI integration |
references/security-testing.md |
Security testing — SAST/DAST/dependency audit, OWASP Top 10 test patterns, container scanning, CI gates |
Core Principles
If it isn't tested, it's broken — Untested code is not working code; it's code whose failure mode hasn't been discovered yet.
Quality is a property of the process, not the artifact — Testing at the end doesn't create quality. Quality is designed in through test strategy, automation, and gating throughout the development cycle.
Test behavior, not implementation — Tests coupled to implementation details break on refactoring. Tests coupled to behavior survive it. Prefer testing what the system does, not how it does it.
Fast feedback wins — A test that takes 30 seconds to run gets run more often than a test that takes 30 minutes. Invest in test speed proportional to feedback frequency.
Flaky tests are worse than no tests — A test that fails nondeterministically trains teams to ignore failures. Fix or remove flaky tests on detection.