cloud-image-bake
Bake, select, prove, and safely retire a Cloud Worker image with crabbox and config one-liners.
DeepseekModel
官方收录技能
质量 优秀 · 90
v1.0.0
获取
https://deepseekmodel.com/api/download.php?id=openclaw-openclaw-custodian-skills-cloud-image-bake-skill-md&format=skill
下载 .skill
标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用
.skill 文件中 system_prompt 字段的实际内容。
name cloud-image-bake description Bake, select, prove, and safely retire a Cloud Worker image with crabbox and config one-liners. Bake a Cloud Worker image Never print or persist secret values; provider credentials stay in their stores. Never hand-edit config files on disk — profile changes go through openclaw config . Every run ends with the observable Prove result or an exact explanation of why it could not be proven. Snapshots are cheap; unmanaged snapshot sprawl is not. Never delete a provider image without hard operator confirmation. Gather openclaw config get cloudWorkers --json crabbox config show --json crabbox doctor --provider <backend> --json crabbox checkpoint list --json Record the current provider, class, image selection, setup command, and the id of the image being superseded. Confirm the requested tooling and a secret-free bake source. Mutate Lease from the current profile, install and smoke-test the tooling: crabbox warmup --provider <backend> --class <class> --keep --timing-json crabbox run --provider <backend> --id <lease> --no-sync -- bash -lc '<install commands> && <tool> --version' Snapshot per backend: AWS: crabbox checkpoint create --provider aws --id <lease> --mode native --strategy image --wait , inspect it, then crabbox image promote <ami-id> with the matching scope. AWS image selection is owned by the promote catalog. Hetzner: hcloud image create --type snapshot --server <server-id> --description <name> ; there is no crabbox create/promote lifecycle for Hetzner yet, so record the snapshot id explicitly. Firecracker: rebuild and republish the rootfs template through the host's template pipeline; do not snapshot a running microVM as a substitute. Point the profile at the new selection only through validated config writes — confirm the exact key first, dry-run, then write (example for a backend whose settings carry an image field): openclaw config schema --json | jq '.properties.cloudWorkers' openclaw config set cloudWorkers.profiles.<profile>.settings.<imageKey> "<image-id>" --dry-run openclaw config set cloudWorkers.profiles.<profile>.settings.<imageKey> "<image-id>" The bundled crabbox profile currently has no image settings key — AWS selection lives in crabbox image promote ; never invent a config field. Preserve the old image until proof passes. Repair openclaw doctor --non-interactive crabbox doctor --provider <backend> --json Apply openclaw doctor --fix --non-interactive only after approval, then re-read the profile and provider inventory. Prove Lease once from the new image and verify the baked tooling is present and fast: crabbox warmup --provider <backend> --class <class> --timing-json crabbox run --provider <backend> --id <lease> --no-sync -- bash -lc '<tool> --version' crabbox stop --provider <backend> --id <lease> Record warmup total and compare against the pre-bake timing. Then confirm the OpenClaw path end to end: dispatch one session to the profile from a client (Cloud destination) and verify the placement reaches active. If any step fails, roll back the image selection and report the exact blocker. Report Report the profile, backend, new and previous image ids, tooling smoke result, timed warmup before/after, and rollback state. Only after successful proof, show the exact deletion target and get hard operator confirmation, then delete only that superseded snapshot ( crabbox image delete <id> or hcloud image delete <id> ) and verify it is gone. Without confirmation, leave it intact and report cleanup pending. Further reference: https://docs.openclaw.ai/gateway/cloud-workers
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下载的 .skill 包内含以下字段。
| 字段 | 说明 |
|---|---|
| format | 格式标识(skill/v1) |
| skill_id | 技能唯一 ID |
| name | 技能名称 |
| version | 版本号 |
| description | 技能描述 |
| category | 所属分类(数组) |
| trigger_words | 触发词列表 |
| tags | 标签列表 |
| source | 来源标识 |
| source_url | 来源链接(本页地址) |
| exported_at | 导出时间(每次下载生成) |
| system_prompt | 系统提示词正文 |
| model_config | 模型参数:provider / model / temperature / max_tokens / top_p |
| examples | 示例 |
| install_guide | 各平台导入说明(Coze / Dify / Claude / 自定义框架) |