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.
Explorez les skills IA publiés de jfriisj et consultez leurs instructions source.
Skills indexés
9Étoiles des dépôts des skills indexés
0Forks du dépôt
0Moyenne des étoiles par skill indexé
0Les étoiles d’un dépôt peuvent se répéter entre ses skills.
Capture a quick, reproducible snapshot of Docker/Compose logs and container state for debugging. Use when smoke tests fail or you need attachable evidence.
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.
Run quick HTTP health/readiness smoke checks against one or more endpoints. Use to validate a service is up before running deeper E2E tests.
Smoke test an audio upload endpoint using multipart/form-data. Use for quick end-to-end validation of transcription pipelines.
Generate a tiny non-sensitive WAV file using only the Python standard library. Use for deterministic smoke tests without committing real user audio.
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.
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.
Run analyzer MCP tools (Ruff + optional dead-code scan) as a quality gate before QA/UAT/release.
Run Python pytest suites and capture reproducible evidence (command, environment, output) into agent-output artifacts. Use for QA verification, debugging, and pre-release confidence.
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.