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- Claude Code Skills
- Qa Expert
qa-expert_skill
- Python
609
GitHub Stars
2
Bundled Files
2 months ago
Catalog Refreshed
4 months ago
First Indexed
Readme & install
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Installation
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npx veilstrat add skill daymade/claude-code-skills --skill qa-expert- .security-scan-passed181 B
- SKILL.md10.3 KB
Overview
This skill establishes comprehensive QA testing processes for any software project using Google Testing Standards and OWASP security best practices. It provides initialization scripts, templated test cases, bug-tracking formats, quality-metrics calculation, and an optional autonomous LLM execution workflow. The goal is reproducible test suites, objective quality gates, and fast handoffs to third-party QA teams.
How this skill works
The skill bootstraps QA infrastructure with a one-command init script that creates directories, tracking CSVs, templates, and a master prompt for autonomous execution. Test cases follow the AAA pattern (Arrange-Act-Assert) and use P0–P4 severity classification; execution updates a tracking CSV immediately after each test. It calculates pass rates, coverage, bug breakdowns and evaluates predefined quality gates, and includes OWASP Top 10 security tests with a 90% coverage target.
When to use it
- Starting QA for a new or existing project
- Writing standardized, reproducible test cases following AAA
- Executing and tracking test plans with immediate CSV updates
- Filing and classifying bugs using P0–P4 severities
- Calculating QA metrics and evaluating quality gates before release
- Preparing documentation and handoff packages for third-party QA teams
Best practices
- Treat test case documents as the ground truth; use tracking CSVs for execution status only
- Write test cases in AAA format with clear prerequisites and exact steps
- Update TEST-EXECUTION-TRACKING.csv immediately after each test; never batch updates
- Classify bugs accurately (P0–P4) and include environment and repro steps
- Target ≥80% pass rate and ≥80% code coverage; target 90% OWASP coverage for security
- Use the master LLM prompt for autonomous execution to speed up repeatable test runs
Example use cases
- Initialize a QA project and produce a ready-to-run test suite and templates in minutes
- Convert manual test run into LLM-driven autonomous execution that auto-files bugs and generates reports
- Run OWASP Top 10 security checks as part of a release gate to meet 90% mitigation target
- Generate daily and weekly QA reports and metrics dashboards for stakeholders
- Package tests/docs and onboarding guides for a third-party QA team handoff
FAQ
Yes. The master prompt is designed for autonomous LLM-driven execution with auto-resume, auto-tracking, auto-bug filing, and auto-reporting; monitor P0 escalations manually.
How are quality gates enforced?
Metrics scripts calculate pass rate, coverage, and bug counts; all defined gates (test execution, pass rate, P0/P1 thresholds, coverage, security) must pass before release.