Agent skill

System Design Review

by HoangNguyen0403 in HoangNguyen0403/agent-skills-standard

Audit an existing or proposed architecture and return a scored verdict across nine axes, from requirements and capacity evidence to observability and rollout, then convert gaps into a prioritized…

MITAuto-check passedDevOps & Cloud

Install System Design Review

skills CLI
$ npx skills add HoangNguyen0403/agent-skills-standard --skill system-design-review -a claude-code

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

GitHub CLI
$ gh skill install HoangNguyen0403/agent-skills-standard system-design-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/HoangNguyen0403/agent-skills-standard.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/system-design/system-design-review .claude/skills/system-design-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
system-design-review
GitHub stars
572
Token cost
~1.5k tokens
SKILL.md length
721 words
Files
5 (incl. references)
Skills in repo
211
Repo updated
First seen
Licence
MIT

At a glance

Audit an existing or proposed architecture and return a scored verdict across nine axes, from requirements and capacity evidence to observability and rollout, then convert gaps into a prioritized…

  • Works in 6 steps: Establish ground truth first: current… → Score the nine axes against artifacts… → Trace the hottest and the most critical… → …
  • Reviewing a design doc
  • SKILL.md covers Priority: P1 (HIGH), Nine Axes (score each…, Profile-Aware Scoring and Scope-Qualified Semantic Review, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

System Design Review is an agent skill from HoangNguyen0403/agent-skills-standard. Audit an existing or proposed architecture and return a scored verdict across nine axes, from requirements and capacity evidence to observability and rollout, then convert gaps into a prioritized roadmap. Use when reviewing a design doc, auditing a running system, or gating a design.

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `evals/evals.json`, `references/mistakes-table.md` and `references/scorecard.md`).

It sits in DevOps & Cloud, covering Accessibility, Architecture decision records and Observability. The repository describes itself as: A collection of Agent Skills Standard and Best Practice for Programming Languages, Frameworks that help our AI Agent follow best practies on frameworks and programming laguages. The licence is MIT.

When your agent uses it

  • Reviewing a design doc
  • Auditing a running system
  • Gating a design

Example prompts

  • “/system-design-review”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Establish ground truth first: current traffic, data volume, incident history, and the top pain the owner reports.
  2. Score the nine axes against artifacts and metrics; mark any unverifiable claim UNVERIFIED.
  3. Trace the hottest and the most critical path end to end; the worst hop is the real bottleneck.
  4. List findings as severity - axis - evidence - consequence - smallest fix.
  5. Convert findings into a roadmap: stop-the-bleeding now, structural next, optional later.
  6. Check operability: who runs this at 3am, which team owns which piece, and whether that team can actually operate it.

What it can do on your machine

Read from SKILL.md and the folder at commit b529c2d. 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

System Design Review loads about 1.5k tokens when it runs, and up to ~6.5k if it reads all its reference files. Until then it costs about 76 tokens; SKILL.md has 721 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~76
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.5k

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 HoangNguyen0403/agent-skills-standard at commit b529c2d, republished under its MIT licence (© HoangNguyen0403). 721 words, ~1,506 tokens.

Download SKILL.mdSave it as .claude/skills/system-design-review/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
system-design-review
description
Audit an existing or proposed architecture and return a scored verdict across nine axes, from requirements and capacity evidence to observability and rollout, then convert gaps into a prioritized roadmap. Use when reviewing a design doc, auditing a running system, or gating a design.

System Design Review

Priority: P1 (HIGH)

Score claims against evidence appropriate to the declared review scope. A proposed design may support a design-readiness verdict through stated mechanisms and planned validation; it cannot claim operational readiness from plans alone. An implementation review requires implementation evidence; an operations claim requires production runtime/deployment evidence.

Nine Axes (score each applicable axis 0-10)

AxisScores 10 whenScores 0 when
RequirementsFunctional, NFR, and out-of-scope written with ownersOnly a feature description exists
Capacity evidencePeak QPS, storage, and bandwidth computed and currentNumbers absent or older than the last traffic change
RedundancyFailure domains, recovery mechanisms and ownership fit the stated objective; proposals include validation criteria, operations claims require measured drillsCritical SPOF or no viable recovery for the stated objective
Data scalingAccess patterns mapped, ownership single, growth path statedOne shared store, no growth plan, unbounded tables
CachingHot read paths cached with TTL and invalidation definedNo cache on a proven hot path, or uninvalidatable cache
Async offloadSlow/bursty work is isolated when required by stated SLO or failure constraints, with bounded drain/recovery; bounded synchronous work is valid when it meets themRequired isolation is absent or synchronous coupling violates the stated constraints
ObservabilitySignals, alert ownership, runbooks and validation fit the declared scope; operations claims require observed telemetryNo relevant signals, owner or response path for a material risk
RolloutCanary or flag with metric rollback trigger and reversible migrationsBig-bang deploy, irreversible migration
Cost proportionalitySpend is sized to the traffic and the risk, and someone can state itTopology bought for an imagined scale nobody measured

Report each applicable axis with evidence and a declared profile weighting. Use an applicable-axis denominator (10 × applicable-axis count), not a fixed /90, when an axis is justified N/A.

Profile-Aware Scoring

  • Declare the system profile and weighting before scoring. An axis may be N/A only when the profile and evidence show that it is outside the system's risk envelope; record the rationale, exclude it from the denominator, and do not silently convert it to zero.
  • Do not reward adding a cache, queue, replica, or region by vocabulary alone. A component earns credit only when a measured constraint, invariant, owner, cost, and failure/recovery behavior require it; unjustified machinery lowers cost proportionality and operability.
  • Review HLD and LLD as one trace: requirements and shaping decisions must resolve into component ownership, contracts, verification, and a stated changed-constraint trigger. A diagram is optional when prose answers the question.
  • Separate lifecycle (proposed|implemented|retired), source kind (code|document|runtime|deployment), and evidence confidence (unverified|assumed|documented|observed). Code/document citations are documented, not deployment proof; runtime/deployment captures may be observed. assumed and unverified carry no citation; explicit citations require evidence_kind.
Show full SKILL.md (278 more words)Show less

Scope-Qualified Semantic Review

Lexical checks are smoke signals, not proof of a sound design. Apply the independent behavioral rubric in semantic evaluation. Record missing calculations, mechanisms, adverse timelines, invariants, recovery, and scope-specific evidence as findings even when expected vocabulary appears.

Review Method

  1. Establish ground truth first: current traffic, data volume, incident history, and the top pain the owner reports.
  2. Score the nine axes against artifacts and metrics; mark any unverifiable claim UNVERIFIED.
  3. Trace the hottest and the most critical path end to end; the worst hop is the real bottleneck.
  4. List findings as severity - axis - evidence - consequence - smallest fix.
  5. Convert findings into a roadmap: stop-the-bleeding now, structural next, optional later.
  6. Check operability: who runs this at 3am, which team owns which piece, and whether that team can actually operate it.

Common Mistakes to Check

  • Architecture drawn before requirements or numbers existed.
  • Redundancy claimed but sharing one config plane, credential, or control plane.
  • Cache added over a query that was never optimized.
  • Sharding adopted before indexing, replicas, and caching were exhausted.
  • Queue with no drain-rate budget, no DLQ, and alerting on depth rather than age.
  • Alerts on CPU rather than user-visible symptoms or error-budget burn.
  • Migration and code shipped as one irreversible step.

Anti-Patterns

  • No score without evidence: cite the metric, artifact, or drill; otherwise mark UNVERIFIED.
  • No rewrite recommendation by default: prefer the smallest fix that removes the proven bottleneck.
  • No uniform severity: rank by user impact and reversibility, not by axis order.
  • No finding without a next action: every gap gets an owner-ready fix.

References

  • Scorecard - scoring rubric, weighting guidance, report template
  • Mistakes Table - failure symptom, root cause, and corrective action

© HoangNguyen0403, MIT. 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 4 other files (references) in skills/system-design/system-design-review of HoangNguyen0403/agent-skills-standard.

  • SKILL.md
  • evals/evals.json
  • references/mistakes-table.md
  • references/scorecard.md
  • references/semantic-evaluation.md

Open the folder on GitHubat commit b529c2d

Compare with similar skills

System Design Review next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

System Design Review compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
System Design Review this skillHoangNguyen0403/agent-skills-standard572—~1.5kAutomated safety check: PassMIT
Ad Architecturealexandremendoncaalvaro/CorridorKey-Runtime7561 repos~1.3kAutomated safety check: PassCustom licence
Otel Nodemizchi/skills360—~1.3kAutomated safety check: PassNone
Opentelemetrymizchi/skills360—~1.3kAutomated safety check: PassNone
Rfc Writermohitagw15856/pm-claude-skills1.4k—~4.1kAutomated safety check: PassMIT
Motel Debugkitlangton/motel298—~2.2kAutomated safety check: PassMIT

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Questions about System Design Review

What does System Design Review do?

Audit an existing or proposed architecture and return a scored verdict across nine axes, from requirements and capacity evidence to observability and rollout, then convert gaps into a prioritized…. System Design Review is an agent skill from HoangNguyen0403/agent-skills-standard. Audit an existing or proposed architecture and return a scored verdict across nine axes, from requirements and capacity evidence to observability and rollout, then convert gaps into a prioritized roadmap.

When should I use System Design Review?

System Design Review fits situations like: reviewing a design doc; auditing a running system; gating a design.

How do I install System Design Review in Claude Code?

Run `npx skills add HoangNguyen0403/agent-skills-standard --skill system-design-review -a claude-code`. Or copy the skill folder (skills/system-design/system-design-review in HoangNguyen0403/agent-skills-standard) into .claude/skills/system-design-review in your project. Claude Code loads it when a task matches its description.

How do I install System Design Review in Codex?

Run `npx skills add HoangNguyen0403/agent-skills-standard --skill system-design-review -a codex`. Or copy the skill folder (skills/system-design/system-design-review in HoangNguyen0403/agent-skills-standard) into .agents/skills/system-design-review in your project. Codex loads it when a task matches its description.

Can I use System Design 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 HoangNguyen0403/agent-skills-standard --skill system-design-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/system-design-review, .gemini/skills/system-design-review, .github/skills/system-design-review and .opencode/skills/system-design-review in your project.

What does System Design Review need to run?

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

Does System Design 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 System Design 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 System Design Review use?

System Design Review is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does System Design Review use?

About 1.5k tokens (SKILL.md is roughly 6k 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 5k tokens, read only when the agent opens those files.

What are the alternatives to System Design Review?

Skills that share tags, products or a category with System Design Review: Ad Architecture (alexandremendoncaalvaro/CorridorKey-Runtime, 756 stars), Otel Node (mizchi/skills, 360 stars), Opentelemetry (mizchi/skills, 360 stars) and Rfc Writer (mohitagw15856/pm-claude-skills, 1.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains System Design Review?

HoangNguyen0403 (a GitHub user) maintains it in HoangNguyen0403/agent-skills-standard, which has 572 GitHub stars. The repository holds 211 skills in this directory. The repository was last updated on October 9, 2026.

Source: HoangNguyen0403/agent-skills-standard on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.