generating-test-reports
This Claude Code skill transforms raw test artifacts like pytest and JUnit outputs into professional, readable test reports. Use it when stakeholders need summarized pass/fail status, coverage metrics, and actionable failure analysis rather than raw debugging logs, typically for QA, release, or review documentation.
git clone --depth 1 https://github.com/foryourhealth111-pixel/Vibe-Skills /tmp/generating-test-reports && cp -r /tmp/generating-test-reports/bundled/skills/generating-test-reports ~/.claude/skills/generating-test-reportsSKILL.md
# Test Report Generator ## Purpose Use this skill when the next deliverable is a readable test report rather than another round of debugging. ## When to Use Use this skill when: - Summarizing pass/fail status, flaky tests, or coverage output for others to read - Turning raw `pytest`, JUnit, or coverage artifacts into a concise report - Producing release, QA, or review-facing test documentation ## Not For / Boundaries - Root-cause debugging of a failure: use `systematic-debugging` - Code review of the underlying implementation: use `code-reviewer` - Implementing a new test suite from scratch: use `tdd-guide` ## Typical Outputs - Test execution summary with totals and failure clusters - Coverage snapshot and quality-gate status - Follow-up action list for the most important failures ## Related Skills - `systematic-debugging` before report packaging if failures are still unexplained - `verification-before-completion` when the report is part of a completion gate
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
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