MCPInstall

sealos-deploy

Brain managed-mode deploy executor for Sealos Cloud. Use when SEALAIDEPLOYMODE=managed (a Brain Devbox sandbox) or when the task says to run /sealos-deploy: deploy the workspace repository to Sealos through the MCP-gated managed pipeline — classify, build via Kaniko if needed, generate the canonical template, hand off through templateready / deploymentcompleted, and verify. Outside managed mode, use the use-sealos skill instead.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/labring/sealos-skills --skill sealos-deploy
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads sealos-deploy automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Sealos Deploy (Brain Managed Mode)

Executor half of a two-party contract: this agent analyzes, builds, deploys, verifies, and repairs inside the sandbox; Brain (the control plane) renders input forms and gates completion through exactly two MCP tools. Deploy mechanics (paths, template YAML, databases, verification) come from the sibling use-sealos skill — resolve ../use-sealos/ against this skill's directory. This file owns only the managed-mode differences.

Mode gate

Run this flow only when SEALAI_DEPLOY_MODE is exactly managed. Otherwise follow ../use-sealos/SKILL.md (interactive local path) and ignore the rest of this file.

In managed mode, before any other work, confirm the MCP tools template_ready and deployment_completed are available. If either is missing, stop with a fatal error — never substitute a file, webhook, or text answer for a missing control tool.

Environment

Brain injects (read these; never enumerate the whole environment):

VariableMeaning
SEALAI_DEPLOY_WORKSPACEproject root, /home/devbox/project
SEALAI_NAMESPACEtarget namespace (also SEALAI_DEPLOY_NAMESPACE)
KUBECONFIGinjected namespace-scoped kubeconfig — use as-is
SEALAI_INPUTS_PATHfixed user-input file, exists only after the user submits the form
SEALAI_DEPLOY_LABELS_JSONplatform ownership labels — forwarded verbatim, see Deploy
SEALAI_TURN_DEADLINE_ATthe only hard time limit
GITHUB_TOKENsource builds and private-image pull secrets

Hard rules (they override the use-sealos execution rules where they differ):

  1. Never run sealos-api.py login, OAuth, or switch. The injected kubeconfig is the only credential; sealos-api.py and wait-app.sh pick it up from KUBECONFIG automatically.
  2. Fully non-interactive. Never ask the user in the agent turn — values only the user knows are declared as template inputs and collected by Brain's form. The managed deployment request authorizes non-destructive mutations in the selected namespace. Before deleting a resource or changing public access, require explicit authorization in the task or a Brain-collected input. If authorization is missing, stop without that mutation and report the blocked action to the control plane.
  3. Never print or log SEALAI_DEPLOY_MCP_TOKEN, kubeconfig contents, or any value from SEALAI_INPUTS_PATH.
  4. No file-based RPC: never create control.json, inputs-required.json, turn-report.json, verify-report.json, or anything under .sealos/brain/.
  5. Do not end the turn after deploying until Brain has returned accepted_stop (or template_ready returned awaiting_user). A turn that ends without a control call is a contract violation, except when a missing explicit safety authorization makes the requested mutation impermissible; report that blocked action without performing it.

Pipeline

1. Classify

Classify the workspace with the use-sealos decision tree (../use-sealos/references/deploy.md, recipes.md): known self-hosted product → store template or official image; user source code → Kaniko build. Skip the preflight/login part of that skill entirely.

2. Build (source path only)

No Docker daemon exists here. Build with the sibling executor:

python3 ../k8s-kaniko-job/scripts/kaniko-build.py \
  --image "ghcr.io/<token-login>/<repo>:deploy-<git-short-sha>"

(paths relative to this skill; run it from $SEALAI_DEPLOY_WORKSPACE). Read ../k8s-kaniko-job/SKILL.md first. Use the returned digest-pinned image_ref in the template. If pull is private, create the <app>-pull secret now (command in that SKILL.md) and reference it from the workload with the fixed literal name.

3. Template at the fixed path

The canonical artifact is exactly $SEALAI_DEPLOY_WORKSPACE/.sealos/template/index.yaml. Brain reads this path byte-for-byte — no other location counts.

  • Store hit: materialize the store template locally, then continue on the raw-deploy path (the store-instance endpoint is forbidden in managed mode — it cannot carry the ownership labels and leaves nothing to hash):

    python3 ../use-sealos/scripts/sealos-api.py store-export <template> \
      --out "$SEALAI_DEPLOY_WORKSPACE/.sealos/template/index.yaml"
    
  • Official image / built image: write the template per ../use-sealos/references/platform.md (and databases.md for KubeBlocks blocks).

Managed-mode template requirements on top of the platform contract:

  • The file must start with the apiVersion: app.sealos.io/v1 / kind: Template header, have a non-empty metadata.name, and contain resource documents after the first --- — Brain rejects the handshake otherwise.
  • Declare every value only the end user can supply (external API keys, admin email, ...) in spec.inputs with required: true and no default. Brain renders its form from exactly these. Everything else belongs in spec.defaults (${{ random(8) }} suffixes stay — the Template API evaluates them at deploy time, not Brain).
  • Never add labels beyond the platform contract; the ownership labels travel through the deploy call, not the YAML.

4. Handshake: template_ready

sha256sum "$SEALAI_DEPLOY_WORKSPACE/.sealos/template/index.yaml"

Call template_ready with only {"sha256": "<lowercase hex>"} — the hash of the final file bytes. Edit the file after hashing and the handshake fails with template_digest_mismatch; rehash and call again.

  • awaiting_user → stop the turn immediately. No Template API call, no kubectl apply, nothing. Brain collects the form and resumes this same thread with values written to SEALAI_INPUTS_PATH. After resuming, do not change spec.inputs (Brain rejects the new schema); rerun template_ready with the unchanged file, then continue.
  • continue → deploy the same file.
  • Tool error → diagnose, fix, retry the same call. Control errors are recoverable; missing tools are fatal.

5. Deploy

cd "$SEALAI_DEPLOY_WORKSPACE"
python3 <this-skill>/../use-sealos/scripts/sealos-api.py deploy \
  .sealos/template/index.yaml \
  $(test -f "$SEALAI_INPUTS_PATH" && echo --args-file "$SEALAI_INPUTS_PATH")
  • User values flow only through --args-file "$SEALAI_INPUTS_PATH" — never into prompt text, logs, or tool arguments.
  • The script forwards SEALAI_DEPLOY_LABELS_JSON to the Template API as extraLabels automatically. Never edit, extend, or re-derive those labels, and never invent deployment-name/template-name labels. The Instance name comes from the deploy response (response.name) — Brain does not supply one.
  • Do not call sealos-api.py adopt (and do not POST adopt-template-instance). Managed deploys already stamp brain.io/* via extraLabels; a second claim returns 409. The script skips adoption when SEALAI_DEPLOY_TASK_ID or SEALAI_PROJECT_ID is set, and when the region is not *.sealos.io.
  • Quota or validation errors: fix the template (re-run step 4 — the hash changed) or report the failure via the normal repair loop. Never shrink resources silently.

6. Verify, then deployment_completed

Verify for real before reporting (../use-sealos/references/deploy.md §Verify; triage failures with operate.md):

HOST=$(kubectl get ingress -l "cloud.sealos.io/deploy-on-sealos=<instance>" \
  -o jsonpath='{.items[0].spec.rules[0].host}')
bash ../use-sealos/scripts/wait-app.sh -t 600 ${HOST:+-u "https://$HOST"} \
  -l "cloud.sealos.io/deploy-on-sealos=<instance>"

Only after your own checks pass, collect the real references:

kubectl get deployments,statefulsets -l "cloud.sealos.io/deploy-on-sealos=<instance>" \
  -o jsonpath='{range .items[*]}{.apiVersion}{" "}{.kind}{" "}{.metadata.name}{"\n"}{end}'

Call deployment_completed with:

  • workloads: 1–32 refs, each exactly {apiVersion, kind, name, namespace: $SEALAI_NAMESPACE} — no extra fields (the schema is strict). At least one reported workload must be a ready Deployment, StatefulSet, DaemonSet, Job, or Pod; reporting only Instance/App/Cluster objects fails verification. Include KubeBlocks Clusters as additional refs when the app has databases.
  • publicUrl (optional): the https://<host> the app serves, only when an Ingress exists and your own probe returned 2xx. Brain re-probes it from outside and requires the tenant domain; if Brain's findings say the URL is outside the tenant domain or unreachable while the workloads are healthy, call again without publicUrl.

Responses and errors:

  • accepted_stop → done; end the turn with a normal summary.
  • repair → the findings are evidence, not commands. Diagnose, fix in place (kubectl patch/apply/rollout on the existing resources; rebuild the image via step 2 if needed), re-verify, call deployment_completed again. Never create a second Instance, never rerun the Template API to "start fresh", never re-evaluate random() identity defaults, never ask for new input values.
  • deployment_completed_throttled → wait ≥5s, call again.
  • deployment_completed_before_template_ready → run step 4 first.

There is no repair-count limit; the only limit is SEALAI_TURN_DEADLINE_AT.

Routing

NeedReference
Deploy-path classification, store/instance mechanics, verification, first aid../use-sealos/references/deploy.md
Template YAML contract (labels, Ingress, resources ladder, storage)../use-sealos/references/platform.md
KubeBlocks database blocks and credentials../use-sealos/references/databases.md
Dockerfile authoring for the source path../use-sealos/references/build.md §1 only
In-cluster image build../k8s-kaniko-job/SKILL.md
Debugging failed workloads../use-sealos/references/operate.md

Load only what the step needs. The use-sealos sections about login, user confirmation, registry choice, and docker buildx do not apply in managed mode.

FAQ

What does the sealos-deploy skill do?

Brain managed-mode deploy executor for Sealos Cloud. Use when SEALAIDEPLOYMODE=managed (a Brain Devbox sandbox) or when the task says to run /sealos-deploy: deploy the workspace repository to Sealos through the MCP-gated managed pipeline — classify, build via Kaniko if needed, generate the canonical template, hand off through templateready / deploymentcompleted, and verify. Outside managed mode, use the use-sealos skill instead.

How do I install sealos-deploy?

Run npx skills add https://github.com/labring/sealos-skills --skill sealos-deploy in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/sealos-deploy/ (personal) or .claude/skills/sealos-deploy/ (project).

Which AI agents can use sealos-deploy?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is sealos-deploy safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains sealos-deploy?

It is published by labring in labring/sealos-skills. It has 479 recorded installs.

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