Cloud Environment Control (plan / apply / drift / rotate / decommission)

Purpose

Manage cloud environment configuration under the repo-env-contract SSOT model, with a strict plan → approval → apply → verify workflow.

The env-cloudctl skill:

•
computes desired runtime configuration from:
- •env/contract.yaml
- •env/values/<env>.yaml
- •env/secrets/<env>.ref.yaml (refs only)
- •docs/project/policy.yaml (routing + auth/preflight + cloud targets)
•produces a deterministic change plan (diff)
•applies changes only after explicit approval
•detects drift
•rotates secrets (backend-dependent)
•decommissions environments (high risk)
•supports env-file injection via envfile provider (local or ssh transport)

Hard preconditions

•
Env SSOT mode is repo-env-contract.
- •Check: docs/project/env-ssot.json
•
Policy SSOT exists and includes a matching cloud target.
- •Required: docs/project/policy.yaml
- •Required: policy.env.cloud.targets[] must match the requested --env (and optional --workload)

If either is not true, STOP.

If docs/project/env-ssot.json, docs/project/policy.yaml, or env/contract.yaml does not exist (first-time setup), run:

bash

python3 -B -S .ai/skills/features/environment/env-contractctl/scripts/env_contractctl.py init --root .

Then customize the contract, policy targets, and secret backends before using cloud operations.

When to use

Use when the user asks to:

•deploy or update configuration for staging/prod
•preview changes (plan/diff) before a release
•check configuration drift
•rotate or revoke secrets
•decommission an environment

Avoid when:

•you need to change the contract schema (use env-contractctl)
•the issue is only local-machine bootstrap (use env-localctl)

Invariants

•MUST NOT request users to paste secrets into chat.
•MUST NOT materialize secret values in evidence artifacts.
•MUST do a plan/diff before any apply.
•MUST require explicit approval before apply/rotate/decommission.
•MUST require --approve-remote before any SSH/SCP remote command.
•
MUST treat Identity/IAM changes as out of scope for automatic apply.
- •You may generate a runbook or policy diff, but do not apply permissions changes automatically.

Inputs

•Contract: env/contract.yaml
•Values: env/values/<env>.yaml
•Secret refs: env/secrets/<env>.ref.yaml
•Policy: docs/project/policy.yaml

Outputs (evidence + context)

Evidence directory

Choose one evidence location (no secrets):

•
Recommended:
- •dev-docs/active/<task-slug>/artifacts/env-cloud/
•
Otherwise:
- •.ai/.tmp/env-cloud/<run-id>/

Evidence files (templates available in ./templates/):

•00-target-and-scope.md
•01-drift-report.md
•02-apply-plan.md
•03-execution-log.md
•04-post-verify.md
•05-context-refresh.md

Context artifacts (safe for LLM)

•docs/context/env/effective-cloud-<env>.json (redacted)

Steps

Phase 0 — Confirm scope

•Confirm target env (must be explicit): staging / prod / other.
•Confirm preconditions (SSOT mode + policy cloud target).
•Choose evidence directory.

Phase A — Plan (read-only)

•Produce a deterministic plan (diff):

bash

python3 -B -S .ai/skills/features/environment/env-cloudctl/scripts/env_cloudctl.py plan --root . --env <env> --workload <optional> --out <EVIDENCE_DIR>/02-apply-plan.md

Remote read (ssh transport only):

bash

python3 -B -S .ai/skills/features/environment/env-cloudctl/scripts/env_cloudctl.py plan --root . --env <env> --workload <optional> --remote --approve-remote --out <EVIDENCE_DIR>/02-apply-plan.md

•Record 00-target-and-scope.md and summarize high-risk operations.

Approval checkpoint (mandatory)

•Ask for explicit user approval before apply, confirming:

•target env
•change summary
•rollback expectations
•whether the change is within an approved maintenance window

Phase B — Apply (write)

•Apply the plan (requires --approve):

bash

python3 -B -S .ai/skills/features/environment/env-cloudctl/scripts/env_cloudctl.py apply --root . --env <env> --workload <optional> --approve --out <EVIDENCE_DIR>/03-execution-log.md

For ssh transport, add --approve-remote.

Phase C — Verify

•Verify desired == deployed (read-only):

bash

python3 -B -S .ai/skills/features/environment/env-cloudctl/scripts/env_cloudctl.py verify --root . --env <env> --workload <optional> --out <EVIDENCE_DIR>/04-post-verify.md

Remote hash check (ssh transport only):

bash

python3 -B -S .ai/skills/features/environment/env-cloudctl/scripts/env_cloudctl.py verify --root . --env <env> --workload <optional> --remote --approve-remote --out <EVIDENCE_DIR>/04-post-verify.md

Phase D — Drift detection

•Detect drift anytime:

bash

python3 -B -S .ai/skills/features/environment/env-cloudctl/scripts/env_cloudctl.py drift --root . --env <env> --workload <optional> --out <EVIDENCE_DIR>/01-drift-report.md

Remote read (ssh transport only):

bash

python3 -B -S .ai/skills/features/environment/env-cloudctl/scripts/env_cloudctl.py drift --root . --env <env> --workload <optional> --remote --approve-remote --out <EVIDENCE_DIR>/01-drift-report.md

Phase E — Secret rotation (backend dependent)

•Rotate a secret (requires --approve):

bash

python3 -B -S .ai/skills/features/environment/env-cloudctl/scripts/env_cloudctl.py rotate --root . --env <env> --workload <optional> --secret <secret_ref_name> --approve --out <EVIDENCE_DIR>/03-execution-log.md

Phase F — Decommission (high risk)

•Decommission an environment (requires --approve):

bash

python3 -B -S .ai/skills/features/environment/env-cloudctl/scripts/env_cloudctl.py decommission --root . --env <env> --workload <optional> --approve --out <EVIDENCE_DIR>/03-execution-log.md

Verification

• SSOT mode is repo-env-contract
• Policy cloud target exists for the env/workload
• Plan produced and reviewed before apply
• Explicit approval gate respected
• Verify passes after apply
• No secret values in evidence
• Central test suite passes: node .ai/tests/run.mjs --suite environment

Boundaries

•MUST NOT modify env/contract.yaml as part of the env-cloudctl workflow.
•MUST NOT apply IAM/Identity changes automatically.
•MUST NOT log secret values.