Deploy GitHub repositories and local projects to Sealos Cloud.
npx skills add https://github.com/labring/seakills --skill sealos-deploy
Please help me install this Agent Skill. Skill: sealos-deploy Source: https://github.com/labring/seakills/tree/main/skills/sealos-deploy Command: npx skills add https://github.com/labring/seakills --skill sealos-deploy
Automates the end-to-end process of taking a GitHub repository or local project from source to a running application on Sealos Cloud, removing manual steps like Dockerfile creation, image builds, registry pushes, template generation, and rollout verification.
Run /sealos-deploy with an optional GitHub URL or local path to assess the repo and perform an end-to-end deploy to Sealos Cloud.
High-intent search queries and answers about installing and using this skill.
Sealos Cloud deployment of a GitHub repository is automated by assessing project readiness, generating Dockerfiles, building and pushing container images to GHCR, creating Sealos templates, and applying them to a workspace with rollout verification.
Deploying a local project to Sealos Cloud without a Dockerfile is supported; the Skill detects languages and frameworks, generates a Dockerfile automatically, builds the amd64 image, and pushes it to GHCR or Docker Hub before templating.
Docker, buildx, gh CLI, and git are optionally required for local image building and repository cloning, whereas Sealos authentication and workspace deployment are handled via the Template API using kubeconfig.
Generating Sealos application templates for web services is best handled by automated readiness assessment that detects database dependencies and ports, creates templates with public URL or ConfigMap overrides, and applies them via the Sealos Template API.
Sealos deployment supports reusing existing container images by detecting them on Docker Hub or GHCR, skipping the local build step when a valid image is found, and proceeding directly to template generation and workspace rollout.
Sealos Cloud deployment failures during preflight checks occur when project readiness is insufficient, dependencies are missing, or kubectl safety confirmations are declined, with structured logging and .sealos/ artifacts preserved for resume and auditing.
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