Agent skill · DevOps & Cloud

wa-guardrails

Generate preventive Well-Architected guardrails — AWS Config rules, Service Control Policies, permission boundaries, CloudWatch alarms, and IaC policy checks (CDK Aspects, cfn-guard, OPA/Sentinel) — plus an optional governance steering doc, so a workload stays aligned with Well-Architected best practices over time instead of being assessed once. Use when the user wants to enforce best practices in CI, prevent insecure or non-compliant configurations from shipping, detect configuration drift, codify the fixes from a Well-Architected review as ongoing controls, or capture standards as an always-

AWS Samples169★ · 1 repos on radarProfile →
claude-codeclinecodexcursorcopilotwindsurfMIT-0
Install
npx skills add aws-samples/sample-well-architected-skills-and-steering --skill wa-guardrails --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 4
SKILL.md size: 11 KB
Bundled scripts: none
Version: 1.0.0
Path: skills/wa-guardrails/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 233
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Well-Architected Guardrails This skill generates **preventive and detective controls** that keep a workload Well-Architected over time. Unlike the assessment skills (which find gaps) or remediation (which fixes a specific finding once), guardrails codify best practices so non-compliant changes are blocked or flagged automatically — in CI, at deploy time, and continuously in the account. **What you'll produce:** ready-to-commit control files (Config rules, SCPs, CI policy checks, alarms), each tied to the WA Question/Best Practice ID it enforces, with a note on whether the control is **preventive** (blocks the bad change) or **detective** (flags it after the fact). ## Step 1: Gather context Ask the user (skip any already provided or inferable from the codebase): > I can generate guardrails to keep your workload Well-Architected. Let me know: > - **Workload name** and code packages/directories (IaC, CI/CD configs) > - **IaC dialect**: CDK (which language), CloudFormation, Terraform, SAM, or mixed > - **Source of controls**: a prior `/wa-review` or assessment output, specific concerns, or "scan and propose" > - **Enforcement points available**: CI pipeline (which one), AWS Organizat

What's inside
Steps it walks through
  1. Step 1: Gather context
  2. Step 2: Discovery — what to enforce
  3. Step 3: Select preventive vs. detective for each control
  4. Step 4: Generate the controls
  5. Step 5: Produce the guardrails plan
  6. Step 6: Offer a governance steering doc
  7. Step 7: Offer follow-up
  8. Calibration Guidance
Ships with 3 files
  • evals/evals.json
  • evals/triggering.json
  • metadata.json
More from sample-well-architected-skills-and-steering
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About this skill
What does the wa-guardrails skill do?

Generate preventive Well-Architected guardrails — AWS Config rules, Service Control Policies, permission boundaries, CloudWatch alarms, and IaC policy checks (CDK Aspects, cfn-guard, OPA/Sentinel) — plus an optional governance steering doc, so a workload stays aligned with Well-Architected best practices over time instead of being assessed once. Use when the user wants to enforce best practices in CI, prevent insecure or non-compliant configurations from shipping, detect configuration drift, codify the fixes from a Well-Architected review as ongoing controls, or capture standards as an always-

How do I install it?

Run `npx skills add aws-samples/sample-well-architected-skills-and-steering --skill wa-guardrails --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From aws-samples/sample-well-architected-skills-and-steering, a repository with 233 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going