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Alibaba Cloud expert guardrails — RAM least-privilege, data boundaries, residency (mainland/international split), cost, and official-source validation. Trigger when designing or reviewing any Alibaba Cloud workload, especially agents or LLMs (Model Studio/Bailian, Qwen,

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$ npx -y skills add jpantsjoha/ai-native-developer-experience --skill alibaba-expert --agent claude-code

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How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/alibaba-expert

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Alibaba Cloud expert guardrails — RAM least-privilege, data boundaries, residency (mainland/international split), cost, and official-source validation. Trigger when designing or reviewing any Alibaba Cloud workload, especially agents or LLMs (Model Studio/Bailian, Qwen,

SKILL.md

alibaba-expert.SKILL.md
name: alibaba-expert
description: Alibaba Cloud expert guardrails — RAM least-privilege, data boundaries, residency (mainland/international split), cost, and official-source validation. Trigger when designing or reviewing any Alibaba Cloud workload, especially agents or LLMs (Model Studio/Bailian, Qwen, AgentScope).

Alibaba Cloud Expert

> **Same discipline, different control plane: RAM and ActionTrail are the guardrails; Model Studio and AgentScope are the agent surface. The mainland/international split is a design input, not an afterthought.**

This skill enforces the discipline that makes Alibaba Cloud workloads production-safe: identity, data boundaries, cost controls, and residency. It is not a feature tour — it is a checklist of the things that cause incidents and compliance failures when skipped.

When to use

  • Designing any Alibaba Cloud infrastructure (new or modified)
  • Before deploying agents or LLM workloads (Model Studio / Bailian, DashScope, PAI, AgentScope)
  • When reviewing a Terraform plan or architecture for an Alibaba Cloud workload
  • When a system touches regulated data or spans mainland-China and international regions

Procedure

1. **Identity and RAM** — verify least-privilege for every principal:

  • RAM roles with STS temporary credentials over long-lived AccessKey pairs. No AccessKeys in code or config.
  • Policies scoped to the specific function; resource groups used to bound blast radius.
  • ActionTrail enabled on all account activity and shipped to a central audit store.

2. **Data boundaries** — for every data store:

  • Classification recorded (public / internal / confidential / regulated — note PIPL and Data Security Law categories where in scope).
  • OSS bucket policies explicit; public access blocked; KMS CMK where required.
  • Cross-account sharing explicit and documented.

3. **Data residency** — for each resource:

  • **Mainland-China vs international accounts are separate control planes** — decide which side the workload and its data live on; regulated mainland data stays in mainland regions.
  • For Model Studio / DashScope calls: confirm the endpoint region matches the residency requirement.

4. **Cost controls** — for every LLM, compute, or storage resource:

  • Budget alerts configured (User Center budgets) at staged thresholds.
  • DashScope token quotas and rate limits set; unbounded agent loops are unbounded spend.
  • Auto-scaling maximums bounded.

5. **Network and egress** — confirm:

  • PrivateLink / PrivateZone used where public endpoints are avoidable.
  • Security groups default-deny; egress costed for cross-border traffic (cross-border egress is materially expensive).

6. **Observability** — confirm:

  • CloudMonitor dashboards and alerts on error rate, latency, and cost.
  • SLS (Log Service) retention configured for audit — evidence before go-live.

7. **Run the Adversarial Gate** — common Alibaba Cloud failure modes: long-lived AccessKeys, public OSS buckets, mainland/international residency confusion, uncapped DashScope spend, missing ActionTrail.

Official sources — validate before you assert

  • Documentation: `alibabacloud.com/help` (international) · `help.aliyun.com` (mainland)
  • Live docs via MCP: official MCP coverage is thinner here than the other vendors — verify what exists before pinning; spring-ai-alibaba ships MCP integrations (`github.com/alibaba/spring-ai-alibaba`).
  • GitHub, foundations: `github.com/aliyun` (incl. `terraform-provider-alicloud` and landing-zone modules)
  • GitHub, agent examples: `github.com/modelscope/agentscope` · `github.com/alibaba/spring-ai-alibaba` · `github.com/QwenLM`
  • Rule: every service/API claim cites an official doc. Service names, quotas, and model IDs are dated facts — stale until re-verified against the source.

Outputs

  • Alibaba Cloud guardrail checklist (pass/fail per item)
  • RAM matrix: principal | role | scope | justification
  • Data classification and boundary map (incl. residency side)
  • Budget alert confirmation
  • Open findings for human review

Guardrails

  • **No long-lived AccessKeys in workloads.** STS or nothing.
  • **Residency is a constraint, not a preference.** The mainland/international split is decided in design, recorded in the ADR.
  • **Budget alerts are not optional.** An unmonitored LLM workload will produce a surprise invoice.
  • **ActionTrail is evidence.** Enable it before go-live, not after an incident.
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