Official agent skill

AWS Well Architected Review

by aws in aws/agent-toolkit-for-aws

Performs a full AWS Well-Architected Framework review evaluating every framework question across all pillars discovered from the live AWS documentation by analyzing code, IaC, and configurations to…

OfficialApache-2.0Auto-check passedDevOps & Cloud

Install AWS Well Architected Review

skills CLI
$ npx skills add aws/agent-toolkit-for-aws --skill aws-well-architected-review -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aws/agent-toolkit-for-aws aws-well-architected-review --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/core-skills/aws-well-architected-review .claude/skills/aws-well-architected-review && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
aws-well-architected-review
GitHub stars
2.8k
Token cost
~3k tokens
SKILL.md length
1,409 words
Files
9 (incl. references, assets)
Skills in repo
138
Repo updated
First seen
Licence
Apache-2.0

At a glance

Performs a full AWS Well-Architected Framework review evaluating every framework question across all pillars discovered from the live AWS documentation by analyzing code, IaC, and configurations to…

  • Works in 8 steps: Define the workload scope → Infrastructure Discovery → Application Architecture Discovery → …
  • Mentions of Well-Architected review
  • SKILL.md covers Overview, Execution model, Step 1: Define the workload… and Step 2: Infrastructure Discovery, plus 8 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

AWS Well Architected Review is an agent skill from aws/agent-toolkit-for-aws, published by the product's own GitHub organization. Performs a full AWS Well-Architected Framework review evaluating every framework question across all pillars discovered from the live AWS documentation by analyzing code, IaC, and configurations to produce evidence-backed findings with Eisenhower-prioritized remediation. Supports full reviews (every framework best practice with BP ID citations), quick reviews (question-level), pillar-scoped reviews, score-mode reviews (a maturity scorecard with per-pillar scores and filtered findings), and lens-specific reviews…

Its SKILL.md is about 3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including reference files and assets (for example `assets/report-template.md`, `references/discovery-procedure.md` and `references/evaluation-procedure.md`).

It sits in DevOps & Cloud, covering Cloud architecture. It works with Amazon Web Services. The repository describes itself as: Official, AWS-supported MCP servers, skills, and plugins to help AI agents build on AWS. The licence is Apache-2.0.

When your agent uses it

  • Mentions of Well-Architected review
  • Pillar assessment
  • Architecture review across pillars
  • Workload assessment

Example prompts

  • “Use the aws-well-architected-review skill to perform a full AWS Well-Architected Framework review evaluating every framework question across all…”
  • “/aws-well-architected-review”

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. Define the workload scope
  2. Infrastructure Discovery
  3. Application Architecture Discovery
  4. Acquire and freeze the live corpus inventory (ACQUIRE_CORPUS gate)
  5. Evaluate EVERY BP against the frozen manifest
  6. Risk Assessment
  7. Produce the report
  8. Offer follow-up

What it can do on your machine

Read from SKILL.md and the folder at commit 2cb0fa1. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

AWS Well Architected Review loads about 3k tokens when it runs, and up to ~12k if it reads all its reference files. Until then it costs about 234 tokens; SKILL.md has 1,409 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~234
When it runs · the whole SKILL.md, loaded when a task matches
~3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~12k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from aws/agent-toolkit-for-aws at commit 2cb0fa1, republished under its Apache-2.0 licence (© aws). 1,409 words, ~2,970 tokens.

Download SKILL.mdSave it as .claude/skills/aws-well-architected-review/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.
name
aws-well-architected-review
description
Performs a full AWS Well-Architected Framework review evaluating every framework question across all pillars discovered from the live AWS documentation by analyzing code, IaC, and configurations to produce evidence-backed findings with Eisenhower-prioritized remediation. Supports full reviews (every framework best practice with BP ID citations), quick reviews (question-level), pillar-scoped reviews, score-mode reviews (a maturity scorecard with per-pillar scores and filtered findings), and lens-specific reviews using lenses discovered from the live AWS documentation. Triggers on mentions of Well-Architected review, WA review, WAR, pillar assessment, architecture review across pillars, workload assessment, cloud readiness evaluation, or a Well-Architected score, grade, or scorecard request. Does not apply to single-pillar deep-dives, learning WA concepts, ADRs, or migration readiness assessments.

Well-Architected Review

Overview

Guides a systematic AWS Well-Architected Framework (WA Framework) review: discover the workload from code and IaC, acquire the live corpus inventory, evaluate every framework question and best practice against evidence, and deliver a risk-ranked, Eisenhower-prioritized report inline.

Framework content is fetched from the live AWS documentation at review time rather than embedded as a snapshot. The AWS MCP server's documentation reader (aws___read_documentation) is recommended for reliable retrieval; when it is unavailable, fetch the same docs.aws.amazon.com pages over HTTPS with the environment's web-fetch tool, and if no documentation access exists at all, proceed from internal knowledge and disclose that the framework inventory could not be verified live. Do not depend on any non-public or internal best-practice/WA-guidance MCP; those are unavailable in supported runtimes.

Detailed procedures live in reference files — read each one when its step says to:

  • Review modes — mode selection (full / quick / pillar-scoped / score), trigger phrases, score output format
  • Discovery procedure — infrastructure and application architecture discovery
  • Live corpus inventory — the gated ACQUIRE_CORPUS stage: deterministic read-only traversal of the framework, the corpus records, and the validation gate
  • Evaluation procedure — evaluating every BP against the frozen manifest, per-pillar passes, aggregation rules, coverage audit
  • Lens guidance — when and how to apply Well-Architected Lenses
  • Risk assessment — impact × likelihood matrix and cross-pillar trade-offs
  • Report template — the full report structure for the report step
  • Security considerations — secure handling of workload data, review tooling, findings, and persisted artifacts

Execution model

Before beginning any step, read and follow security considerations — secrets redaction, HTTPS-only retrieval, least privilege, and confidentiality handling must be loaded before you operate on workload code or review tooling.

A full review runs as a gated sequence. Each step has a transition gate; you MUST NOT advance to the next step, or skip a step, when its gate has not passed. The single user-visible deliverable is one complete inline report — scratch files (a run-local working directory) are execution state only, never the delivered artifact, and their paths MUST NOT appear in the report.

Non-interactive by default. When the user has explicitly requested a review and supplied sufficient scope, execute every step to completion without pausing for confirmation between steps. The discovery and risk-assessment checkpoints are internal validation gates, not user stops: validate them yourself and proceed. Pause for the user only when the user explicitly asked for interactive checkpoints, or when a required scope decision genuinely cannot be inferred (e.g. an ambiguous pillar-scoped request).

Non-negotiable invariants — ALL modes (full / quick / pillar-scoped / score):

  • Step 4 (ACQUIRE_CORPUS) is mode-independent: every mode acquires and validates the live corpus inventory before any assessment and reads its questions/BPs against that frozen manifest. Assessment MUST NOT begin against an incomplete or unvalidated manifest, and no mode may skip Step 4.
  • Canonical IDs only — never fabricate a PILLAR##-BP## ID. If corpus acquisition cannot produce an ID, that is a surfaced error, not a gap to invent around.

Non-negotiable invariants — full review only:

  • Every BP in the frozen manifest receives exactly one status from the five-value vocabulary.
  • All sections of the report template are present (it is the authoritative list — the numbered items in Step 7 are the recall-critical subset, NOT the complete set: the template also mandates the Executive Summary, Architecture Overview, Cross-Pillar Trade-offs, Next Steps, and others). The report is emitted inline, first line # Well-Architected Review:. No "see file", attachment, or scratch-path deferral.

Step 1: Define the workload scope

Establish the workload from what the user provided:

  • Workload name and brief description
  • Code packages/directories to analyze (IaC, application code, CI/CD configs)
  • Business criticality (critical, high, standard, low)
  • Current pain points (optional)

If the user has already provided architecture details or you are in a codebase with IaC, proceed with discovery without prompting. When no code or IaC is available (the user describes their architecture verbally), proceed using the description as evidence; mark findings you cannot verify in code as "Based on description — verify in code." Do NOT ask for code when the user has already given enough context for a meaningful review.

Determine the review mode (full / quick / pillar-scoped / score) from the user's phrasing — read review modes. Determine whether the workload matches a live lens — read lens guidance when one does.

Step 2: Infrastructure Discovery

Read and follow the discovery procedure.

Step 3: Application Architecture Discovery

Continue following the discovery procedure, including its internal completeness gate before evaluation.

Step 4: Acquire and freeze the live corpus inventory (ACQUIRE_CORPUS gate)

Read and follow the live corpus inventory procedure. First create the run-local working directory this review uses for scratch state — the corpus/ folder that holds questions.jsonl, best-practices.jsonl, and manifest.json referenced below. Then build the complete live corpus inventory (the question + best-practice manifest) by a bounded, read-only traversal of the canonical framework pages (prefer aws___read_documentation; see the reference for the non-MCP HTTPS fallback), reduce each page to structured records immediately, and validate the manifest.

Gate: you MUST NOT begin Step 5 until corpus/manifest.json reports valid: true. The frozen manifest is the sole authority for the expected question and BP sets used by evaluation, the coverage audit, and the report.

Show full SKILL.md (571 more words)Show less

Step 5: Evaluate EVERY BP against the frozen manifest

CRITICAL — DO NOT PRODUCE A SHORT REVIEW. The most common failure is citing a subset of BPs and stopping. A full review MUST evaluate every BP in the frozen manifest, each with a status from the five-value vocabulary (with rationale).

Read and follow the evaluation procedure. It defines per-pillar passes against the frozen manifest, aggregation, per-mode adjustments, and the coverage audit (its sub-steps are labelled 5a–5d). For each BP assess:

  • Status: exactly one of "Implemented", "Partially Implemented", "Not Implemented", "Not Applicable", "Cannot Determine"
  • Evidence: specific file paths and line numbers (or "Based on description")
  • Gaps: what is missing or could be improved
  • Risk: what could go wrong due to the gap

Evaluate every pillar in the frozen manifest, using its pillar names, prefixes, and question categories.

Step 6: Risk Assessment

Read and follow the risk assessment procedure, including its internal gate.

Step 7: Produce the report

Mode gate: For score mode, emit only the scorecard output from review modes. For quick and pillar-scoped reviews, apply the mode adjustments from review modes. For a lens-only request (the user named a single WA Lens and did not ask for a full framework review), produce a standalone lens report — the core framework tables are omitted and the deliverable is the Lens Findings section plus a lens scorecard, following lens guidance; when a lens is applied on top of a full review, keep the full structure and add the Lens Findings section. Otherwise — a full review — read the report template and produce the report with that exact structure. The report template is the authoritative list of mandatory sections; the following are the recall-critical ones that a weaker model most often drops (do NOT treat them as the complete set):

  1. Coverage audit (from the evaluation procedure, Step 5d) before the executive summary
  2. Pillar scorecard with per-pillar scores (1-5)
  3. Per-question assessment table — every question in the frozen manifest, no truncation
  4. Full BP Ledger — one row per evaluated BP, concatenated verbatim from the pillar passes
  5. Risk-classified findings (Critical/High expanded, Medium condensed, Low tabular)
  6. Eisenhower-prioritized remediation plan (Do First / Plan / Delegate / Defer) with SMART goals

Emit the report inline as the final response, first line # Well-Architected Review:. Do not defer any section to a file.

Step 8: Offer follow-up

After delivering the report, offer:

Would you like me to:

  • Deep-dive into a specific pillar with expanded analysis?
  • Generate IaC templates to remediate a specific finding?
  • Create a migration plan for a specific architectural change?
  • Compare your workload against a specific WA Lens in detail?
  • Generate automated checks (Config rules, custom metrics) for ongoing compliance?
  • Produce a WA Tool import for tracking in the AWS console?

Calibration Guidance

  • A workload with multi-AZ, encryption, CI/CD with rollback, monitoring, and auto-scaling is MATURE — most findings should be improvements, not Critical
  • Do NOT manufacture Critical findings for a well-built workload — accuracy over alarm
  • When business criticality is "low"/"standard", accept simpler architectures (single-region is fine for internal tools)
  • When business criticality is "critical", apply stricter standards (multi-region DR, chaos testing, sub-minute RTO expected)
  • Every finding MUST have code evidence — no generic recommendations without backing
  • If something cannot be determined from code, say "Cannot Determine" and explain what runtime/interview data is needed
  • Acknowledge strengths prominently — a mature workload should feel validated, not just criticized

Security Considerations

Read and follow security considerations before using review tooling, sharing findings, or persisting artifacts.

© aws, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 8 other files (references, assets) in skills/core-skills/aws-well-architected-review of aws/agent-toolkit-for-aws.

  • SKILL.md
  • assets/report-template.md
  • references/discovery-procedure.md
  • references/evaluation-procedure.md
  • references/lens-guidance.md
  • references/phase-live-inventory.md
  • references/review-modes.md
  • references/risk-assessment.md
  • references/security-considerations.md

Open the folder on GitHubat commit 2cb0fa1

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Categories

Questions about AWS Well Architected Review

What does AWS Well Architected Review do?

Performs a full AWS Well-Architected Framework review evaluating every framework question across all pillars discovered from the live AWS documentation by analyzing code, IaC, and configurations to…. AWS Well Architected Review is an agent skill from aws/agent-toolkit-for-aws, published by the product's own GitHub organization. Performs a full AWS Well-Architected Framework review evaluating every framework question across all pillars discovered from the live AWS documentation by analyzing code, IaC, and configurations to produce evidence-backed findings with Eisenhower-prioritized remediation.

When should I use AWS Well Architected Review?

AWS Well Architected Review fits situations like: mentions of Well-Architected review; pillar assessment; architecture review across pillars; workload assessment.

How do I install AWS Well Architected Review in Claude Code?

Run `npx skills add aws/agent-toolkit-for-aws --skill aws-well-architected-review -a claude-code`. Or copy the skill folder (skills/core-skills/aws-well-architected-review in aws/agent-toolkit-for-aws) into .claude/skills/aws-well-architected-review in your project. Claude Code loads it when a task matches its description.

How do I install AWS Well Architected Review in Codex?

Run `npx skills add aws/agent-toolkit-for-aws --skill aws-well-architected-review -a codex`. Or copy the skill folder (skills/core-skills/aws-well-architected-review in aws/agent-toolkit-for-aws) into .agents/skills/aws-well-architected-review in your project. Codex loads it when a task matches its description.

Can I use AWS Well Architected Review in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aws/agent-toolkit-for-aws --skill aws-well-architected-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/aws-well-architected-review, .gemini/skills/aws-well-architected-review, .github/skills/aws-well-architected-review and .opencode/skills/aws-well-architected-review in your project.

What does AWS Well Architected Review need to run?

SKILL.md names no scripts, command-line tools or credentials: AWS Well Architected Review is instructions for the agent only.

Does AWS Well Architected Review access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is AWS Well Architected Review safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does AWS Well Architected Review use?

AWS Well Architected Review is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does AWS Well Architected Review use?

About 3k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 8.7k tokens, read only when the agent opens those files.

What are the alternatives to AWS Well Architected Review?

Skills that share tags, products or a category with AWS Well Architected Review: Cloud Cost Optimization (wshobson/agents, 40k stars), Thesvg (glincker/thesvg, 2.8k stars), AWS Cloud Advisor (tech-leads-club/agent-skills, 7k stars) and Dangling DNS Finder (anirudhbiyani/findmytakeover, 180 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains AWS Well Architected Review?

aws (a GitHub organization, an official publisher) maintains it in aws/agent-toolkit-for-aws, which has 2,835 GitHub stars. The repository holds 138 skills in this directory. The repository was last updated on October 9, 2026.

Source: aws/agent-toolkit-for-aws on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.