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AWS expert guardrails — IAM least-privilege, data boundaries, cost controls, residency, and official-source validation. Trigger when designing or reviewing any AWS workload, especially agents, LLMs (Bedrock), or multi-account systems.

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

How it fires

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/aws-expert

Context preview

The summary Claude sees to decide when to auto-load this skill.

AWS expert guardrails — IAM least-privilege, data boundaries, cost controls, residency, and official-source validation. Trigger when designing or reviewing any AWS workload, especially agents, LLMs (Bedrock), or multi-account systems.

SKILL.md

aws-expert.SKILL.md
name: aws-expert
description: AWS expert guardrails — IAM least-privilege, data boundaries, cost controls, residency, and official-source validation. Trigger when designing or reviewing any AWS workload, especially agents, LLMs (Bedrock), or multi-account systems.

AWS Expert

> **The Well-Architected pillars are the floor, not the ceiling. On AWS, IAM and cost are where agent workloads blow up first.**

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

When to use

  • Designing any AWS infrastructure (new or modified)
  • Before deploying agents or LLM workloads to AWS (Bedrock, AgentCore, Strands)
  • When reviewing a CloudFormation/CDK/Terraform plan for an AWS workload
  • When a system spans multiple accounts, touches regulated data, or crosses regions

Procedure

1. **Identity and IAM** — verify least-privilege for every role and human principal:

  • No wildcard `Action: "*"` with `Resource: "*"` on any role. Managed policies scoped to the specific function.
  • Roles over IAM users; IRSA for EKS, instance profiles for EC2. No long-lived access keys in workloads.
  • SCPs at the OU level deny sensitive services by default; permission boundaries on delegated admin.
  • CloudTrail enabled on all management and data-plane events, shipped to a log-archive account.

2. **Data boundaries** — for every data store in the design:

  • What data classification does it hold (public / internal / confidential / regulated)?
  • S3 Block Public Access at account level; bucket policies explicit; KMS CMK where required.
  • Cross-account sharing only via explicit resource policy with external ID.
  • Tenant boundaries enforced at the data layer, not just the application layer.

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

  • Region allow-list enforced by SCP, not convention.
  • For Bedrock / LLM calls: regional endpoints; check cross-region inference profiles where residency matters.

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

  • AWS Budgets alerts at 50%, 75%, 90%, 100%.
  • Bedrock invocation quotas/caps and rate limits set; unbounded agent loops are unbounded spend.
  • Autoscaling maximums set; Savings Plans / Spot evaluated where appropriate.

5. **Network and egress** — confirm:

  • PrivateLink / VPC endpoints used where public endpoints are avoidable.
  • Security groups default-deny with explicit allow rules; egress costed for cross-region and internet traffic.

6. **Observability** — confirm:

  • CloudWatch dashboards and alarms on error rate, latency, and cost thresholds.
  • X-Ray tracing on agent/LLM call paths.
  • CloudTrail as audit evidence — enabled before go-live, not after an incident.

7. **Run the Adversarial Gate** — common AWS failure modes: wildcard IAM, public S3, uncapped Bedrock spend, missing CloudTrail data events, global endpoints on residency-sensitive data.

Official sources — validate before you assert

  • Documentation: `docs.aws.amazon.com` · Well-Architected: `docs.aws.amazon.com/wellarchitected`
  • Live docs via MCP (verify currency before pinning): the official `awslabs/mcp` monorepo includes the **AWS Documentation MCP Server** — fetch current docs instead of relying on memory.
  • GitHub, foundations: `github.com/awslabs` · `github.com/aws-ia` · `github.com/aws-samples`
  • GitHub, agent examples: `github.com/strands-agents/sdk-python` · Bedrock agent samples under `github.com/aws-samples`
  • Rule: every service/API claim cites an official doc. Quotas, prices, and model IDs are dated facts — stale until re-verified against the source.

Outputs

  • AWS guardrail checklist (pass/fail per item)
  • IAM matrix: principal | role | scope | justification
  • Data classification and boundary map
  • Budget alert confirmation
  • Open findings for human review

Guardrails

  • **No wildcard actions on wildcard resources.** Ever.
  • **Residency is a constraint, not a preference.** Enforce with SCPs, not conventions.
  • **Budget alerts are not optional.** An unmonitored LLM workload will produce a surprise invoice.
  • **CloudTrail is evidence.** Enable it before go-live, not after an incident.
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Repo: jpantsjoha/ai-native-developer-experience

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