ai-model-nodejs
Use this skill for Node.js backend AI via @cloudbase/node-sdk (>=3.16.0) — cloud functions, CloudRun, Express/Koa/NestJS,…
CloudBase declarative deployment from a cloudbaserc config (声明式部署, 配置式部署, cloudbaserc 部署) through the deployBuild / deployPlan / deployApply MCP tools. Use when deploying database, functions, app, hosting, or gateway resources described in cloudbaserc.json/yaml as a single
Claude Code
$ npx -y skills add TencentCloudBase/CloudBase-AI-Toolkit --skill cloudbase-declarative-deploy --agent claude-code
Codex
$ npx skills add TencentCloudBase/CloudBase-AI-Toolkit --skill cloudbase-declarative-deploy -a codex -y
Cursor
$ npx skills add TencentCloudBase/CloudBase-AI-Toolkit --skill cloudbase-declarative-deploy -a cursor -y
Gemini CLI
$ npx skills add TencentCloudBase/CloudBase-AI-Toolkit --skill cloudbase-declarative-deploy -a gemini-cli -y
GitHub Copilot
$ npx skills add TencentCloudBase/CloudBase-AI-Toolkit --skill cloudbase-declarative-deploy -a github-copilot -y
OpenCode
$ npx skills add TencentCloudBase/CloudBase-AI-Toolkit --skill cloudbase-declarative-deploy -a opencode -y
Windsurf
$ npx skills add TencentCloudBase/CloudBase-AI-Toolkit --skill cloudbase-declarative-deploy -a windsurf -y
name: cloudbase-declarative-deploy description: "CloudBase declarative deployment from a cloudbaserc config (声明式部署, 配置式部署, cloudbaserc 部署) through the deployBuild / deployPlan / deployApply MCP tools. Use when deploying database, functions, app, hosting, or gateway resources described in cloudbaserc.json/yaml as a single desired-state config, when a user wants to build static hosting artifacts locally first (deployBuild), or wants a dry-run plan before applying (deployPlan), or for multi-environment deploys via mode / envOverrides. Covers the build-plan-apply flow (local build → dry-run plan → apply), the deploy-but-never-build contract for app and hosting, reading buildHint (buildCommand / outputDir / artifactReady) from the plan, hosting build-output neutralization, BUILD_OUTPUT_NOT_FOUND recovery, envId resolution priority, only/skip filtering, concurrency, and continueOnError. deployApply builds nothing: use deployBuild for hosting and build app yourself before applying; distinct from per-resource tcb CLI deploys." version: 2.37.6 license: MIT alwaysApply: false
Deploy a whole CloudBase project from one `cloudbaserc` config as **desired state**, using the `deployBuild` (local hosting build), `deployPlan` (dry-run) and `deployApply` (apply) MCP tools. The orchestrator applies resources in a fixed dependency order:
database → functions → app → hosting → gateway
Sibling CloudBase skills ship beside this skill. Use local relative paths such as `../cloudbase-cli/SKILL.md`.
Cloud-hosted MCP mode does not guarantee access to a local workspace filesystem or stable relative paths. If a referenced sibling file is not available in cloud mode, use this skill's embedded guidance as source of truth and ask the user for any missing constraints (or to install the missing skill). Do **not** HTTP-fetch remote skill or protocol markdown into the agent context.
**Cross-cutting protocols** (required before applying any deploy):
resources, and the user wants to deploy them together as one config.
hosting deploys no longer build implicitly — see `deployBuild`).
`deployBuild` / `deployPlan` / `deployApply` in this skill are the **local-form declarative executor**. In cloud-hosted MCP mode they are intentionally not registered, because that runtime has no local `cwd` and no filesystem-bound execution path.
This is an **execution-channel switch, not a capability gap**. Everything still deploys, but the artifact is uploaded first and the build runs in the cloud. If those three tools are missing from the tool list, that is expected — pick the channel that matches the resource.
1. `queryFunctions(action=getFunctionUploadUrl, functionName?)` returns `uploadUrl`, `uploadHeaders`, `cosBucketName`, `cosBucketRegion`, `cosObjectName`, `expiresInSeconds` 2. `PUT` the function zip to `uploadUrl` with `uploadHeaders` 3. `manageFunctions(action=createFunction|updateFunctionCode, code={cosBucketName, cosObjectName, cosBucketRegion?})` — phase B deploys from the environment's own COS bucket (`deployMode=cos`); pass the triple through unchanged, the schema is strict
`contentPath` (a local directory) is rejected in cloud mode. For layer contents use `base64Content`; for code use the two-phase path above.
1. `queryApps(action=getUploadUrl, serviceName=...)` returns `uploadUrl`, `uploadHeaders`, `unixTimestamp` 2. Upload the source/build zip to `uploadUrl` with the returned headers (`Content-Type: application/zip`)
3. `manageApps(action=deployApp, cosTimestamp=<unixTimestamp>, installCmd?, buildCmd?, deployCmd?)`
container; you pass data and declarations, you do not run local shell commands
`manageHosting(action=upload)` is blocked in cloud mode because it needs a local path. Deploy a static site through the CloudApp two-step upload above (upload the prebuilt artifact, exclude `node_modules`). Uploading or downloading an already-hosted file has no remote substitute and needs local mode. The other hosting actions (`delete`, `setWebsiteDocument`, `enableService`, `bindDomain`, `unbindDomain`, `updateDomain`) remain available.
was generated or reviewed in cloud mode; state what is about to be deployed and what the upload contains. Roadmap: upload `cloudbaserc` as a data artifact, then run server-side plan/apply orchestration.
not apply; pass the target environment explicitly.
For parameter details, see `referenc
AI writes the code. CloudBase runs the backend. The CloudBase integration layer for AI coding tools: Plugin installs the stack, Skills steer how code is written, MCP operates databases, functions, storage, and deploys from chat.
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