Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Task automation, containerization, CI/CD, and experiment tracking
Task automation, containerization, CI/CD, and experiment tracking
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Automate tasks, containers, CI/CD, and ML experiments.
Copy justfile: cp references/justfile ../your-project/ Tasks: just check - Run all checks just test - Run tests just build - Build package just clean - Remove artifacts just train - Run training
Multi-stage build: cp references/Dockerfile ../your-project/ docker build -t my-model . docker run my-model Optimizations: Layer caching (uv sync before copy src/) Minimal runtime image Non-root user
Automated pipeline: cp references/ci-workflow.yml ../your-project/.github/workflows/ci.yml Runs on push/PR: Lint (Ruff + MyPy) Test (pytest + coverage) Build (package + Docker)
# Setup task runner cp references/justfile ./ # Setup CI mkdir -p .github/workflows cp references/ci-workflow.yml .github/workflows/ci.yml # Setup Docker cp references/Dockerfile ./ # Test locally just check docker build -t test .
import mlflow mlflow.autolog() with mlflow.start_run(): mlflow.log_param("lr", 0.001) model.fit(X, y) mlflow.log_metric("accuracy", acc)
Converted from MLOps Coding Course
Initial OpenClaw conversion Added justfile template Added Dockerfile Added CI workflow
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Largest current source with strong distribution and engagement signals.