GitHub
docker-logs-snapshot
Capture a quick, reproducible snapshot of Docker/Compose logs and container state for debugging. Use when smoke tests fail or you need attachable evidence.
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jfriisj AI Skills
GitHub ↗浏览 jfriisj 维护的已发布 AI 技能，比较用途与说明，并通过来源仓库了解安装方式。
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9收录技能的仓库 Stars 合计
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0平均每个技能的仓库 Stars
0同一仓库中的多个技能可能共享 Stars，合计包含重复仓库数据。
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GitHub
compose-bringup
Bring up a Docker Compose stack reliably and verify basic service/container status. Use for local smoke tests, live testing, and staging-like bring-up.
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GitHub
http-health-smoke
Run quick HTTP health/readiness smoke checks against one or more endpoints. Use to validate a service is up before running deeper E2E tests.
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GitHub
multipart-audio-smoke
Smoke test an audio upload endpoint using multipart/form-data. Use for quick end-to-end validation of transcription pipelines.
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GitHub
synthetic-wav-sample
Generate a tiny non-sensitive WAV file using only the Python standard library. Use for deterministic smoke tests without committing real user audio.
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GitHub
cpu-mode-assertions-torch
Assert CPU-only runtime inside a container using PyTorch (torch.cuda.is_available()==False) and optional env var checks. Use to prevent accidental GPU execution during CPU smoke tests.
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GitHub
version-audit-quickscan
Quick scan for version strings across common files (README, pyproject, requirements, package manifests) to avoid release blockers from inconsistent versions. Use before tagging or publishing.
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GitHub
python-code-quality-scan
Run analyzer MCP tools (Ruff + optional dead-code scan) as a quality gate before QA/UAT/release.
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GitHub
python-pytest-run-capture
Run Python pytest suites and capture reproducible evidence (command, environment, output) into agent-output artifacts. Use for QA verification, debugging, and pre-release confidence.
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默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。