CloudBase Declarative Deploy
SkillDatabases & dataCloudBase 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 when handling multi-environment deploys via mode / envOverrides. Covers build-plan-apply flow (deployBuild local build → deployPlan dry-run → deployApply confirm=true), hosting build-output neutralization, envId resolution priority, only/skip filtering, concurrency, and continueOnError. Prefer deployBuild (when hosting declares a buildCommand) and deployPlan before deployApply; do not confuse with per-resource tcb CLI deploy or single-function deploy.
Available today. Use it from your connected AI after setup.
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Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the CloudBase Declarative Deploy skill
What this skill tells your AI
The instructions your AI receives, as published by tencentcloudbase/cloudbase-ai-toolkit in config/.claude/skills/cloudbase-declarative-deploy/SKILL.md and read by ahel’s review.
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 skills (local only)
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):
- Change Safety Protocol:
../cloudbase-platform/references/protocols/change-safety-protocol.md - Deployment Gate:
../cloudbase-platform/references/protocols/deployment-gate.md
When to use this skill
- The project has a
cloudbaserc.json/.yaml/.yml/.jsdescribing multiple resources, and the user wants to deploy them together as one config. - The user asks for 声明式部署 / 配置式部署 / "deploy from cloudbaserc" / "deploy the whole project".
- The user wants to preview what a deploy will change before applying (dry-run plan).
- The user wants to build the static hosting artifact locally first (declarative
hosting deploys no longer build implicitly — see
deployBuild). - Multi-environment deploy: production/staging via
mode+envOverrides.
Do NOT use for
- Deploying a single cloud function or one static site via
tcbCLI →../cloudbase-cli/SKILL.md. - In-app SDK integration (web/miniprogram/node) → the matching SDK skill.
- Console UI operations.
Cloud mode
deployBuild / deployPlan / deployApply in this skill are the local-form declarative
executor. In cloud-hosted MCP mode these tools are intentionally not registered
(filtered at tool registration), because that runtime has no local cwd /
filesystem-bound execution path.
If you are in cloud mode and do not see deployBuild / deployPlan / deployApply in the
tool list, this is expected behavior.
Use the cloud upload-channel path instead:
queryApps(action=getUploadUrl)to getuploadUrl,uploadHeaders,unixTimestamp- Upload source/build zip to
uploadUrlwith returned headers- If cloud build requires private/offline dependencies, package
node_modulesexplicitly - For public dependencies, uploading
package.json+ lockfile is typically enough
- If cloud build requires private/offline dependencies, package
manageApps(action=deployApp, cosTimestamp=<unixTimestamp>, installCmd?, buildCmd?, deployCmd?)installCmd/buildCmd/deployCmdare pipeline declarations executed in cloud container- Agent passes data + declarations; it does not execute local shell commands
Planned cloud declarative path (incremental roadmap): upload cloudbaserc as a data
artifact, then run server-side plan/apply orchestration. deployApply remains the
local-form executor of the same declarative spec.
For parameter details, see references/plan-and-apply.md (Cloud-hosted upload pipeline path).
Core principles
-
Plan before apply — always. Run
deployPlanfirst (dry-run, zero side effects). Read the per-resource action classification and show it to the user before callingdeployApply. -
Apply requires explicit confirm.
deployApplywill refuse unlessconfirm=trueis passed. This is the destructive-write guard. -
Deployment Gate. Before any apply, complete
cloudbase-platform/references/protocols/deployment-gate.mdand present the mandatory declaration. -
Conservative on existing resources by default.
yesdefaults tofalse→ existing resources are skipped, not overwritten. Only passyes=truewhen the user explicitly wants to overwrite/update existing resources. -
database failure always aborts. Even with
continueOnError=true, a database-stage failure stops the whole deploy, because later resources depend on it. -
Resolve envId explicitly. Never rely on implicit defaults silently — know which environment is targeted (see the priority table below) and confirm it with the user before applying.
Plan action classification
deployPlan returns a list of resource entries. Each status means:
| status | meaning |
|---|---|
create | new resource, will be created |
update | exists, will be overwritten/updated |
skip | no change needed |
conflict | conflict detected — deploy will abort, must resolve first |
deploy | direct overwrite upload |
If any entry is conflict, stop and resolve it before applying.
envId resolution priority
explicit envId param > cloudbaserc `envId` > logged-in / bound environment
If none can be resolved, the tool errors out. Prefer confirming the resolved envId with the user before applying to production.
Local workflow (build → plan → apply)
When hosting declares a buildCommand, declarative deploy is a three-step flow —
deployApply no longer runs the local build implicitly:
- Ensure a
cloudbasercconfig exists under the project root (cwd). - Build first (only when
hostinghas abuildCommand): calldeployBuild({ cwd, mode? })to produce the local artifacts (builds every hosting item; pure-static items without a build command are skipped automatically).- If the build artifacts are missing at apply time,
deployApplyfails withBUILD_OUTPUT_NOT_FOUNDand directs you back to this step — calldeployBuildfirst, then retry. deployBuildneeds noenvIdand noconfirm(local build only, never touches cloud resources); if dependencies are not installed it fails withDEPENDENCY_NOT_INSTALLEDand tells you to run install first.
- If the build artifacts are missing at apply time,
- Call
deployPlan(optionally withmode,envId,only,skip). Read the plan. - Present the plan + Deployment Gate declaration to the user; get confirmation.
- Call
deployApplywithconfirm=true(plusyes/concurrency/continueOnErroras needed). Reuse the samemode/envId/only/skipas the plan. A hosting item with existing build output is uploaded directly (the tool clears the build command and reportshostingNeutralized: true); rebuild withdeployBuildafter source changes so the upload is not stale. - Report the applied result back to the user.
For cloud-hosted MCP mode, do not ask for local cwd/filesystem reads; use the
Cloud mode upload-channel flow above.
Build & pipeline execution
Use this mental model: build → plan → apply. The build executor depends on resource type.
| resource | typical build executor | deployment path |
|---|---|---|
hosting | deployBuild (local shell build, run before apply) | deployApply uploads the built output directly; missing output → BUILD_OUTPUT_NOT_FOUND |
app (framework=static) | local prebuilt artifact | package upload + deploy record |
app (non-static frameworks) | cloud pipeline | source zip upload + cloud build + deploy |
functions | local zip / cloud build / image pipeline | depends on buildStrategy (zip/cloud/local/image) |
deployBuild builds every hosting item that has a buildCommand (framework mapping or
package.json auto-detection); it skips pure-static items. Build failures surface as
BUILD_FAILED, missing local dependencies as DEPENDENCY_NOT_INSTALLED (run install
first — deployBuild never installs dependencies for you).
Build command resolution follows declaration priority:
explicit config > framework mapping defaults > package.json auto-detection
buildCommand / installCommand / deployCmd are declarative intent in config.
Execution ownership depends on path:
- local-form paths: specific steps may run in local shell executor
- cloud-hosted paths: commands are executed by cloud pipeline container (staticCmd), or replaced by prebuilt artifact upload
So the answer to "can cloud mode run local CLI commands" is: execution authority is moved from local shell to cloud pipeline; agent transmits declarations and artifacts.
Routing
| User task | Read |
|---|---|
| cloudbaserc resource fields & desired-state config shape | references/config-schema.md |
| deployPlan → deployApply two-step flow, parameters, safety | references/plan-and-apply.md |
| Multi-env (mode / envOverrides), envId priority, env vars | references/multi-env.md |
Minimum self-check
- Built the hosting artifacts first (
deployBuild) whenhostingdeclares abuildCommand? - Ran
deployPlanand read the action classification beforedeployApply? - Resolved and confirmed the target
envId? - Completed the Deployment Gate declaration before applying?
- Passed
confirm=trueonly after user confirmation? - Left
yes=falseunless overwrite of existing resources was explicitly requested? - Handled any
conflictentries before applying?
Reference index
All packaged reference files (required for skill lint reachability):
Signals
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- Sep 2026
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cloudbase-declarative-deploy- Source
- github.com/tencentcloudbase/cloudbase-ai-toolkit