/cs-frontend-review

description: Frontend engineering review — walks the 7 Matt Pocock forcing questions (device, LCP target, rendering, bundle budget, SEO vs auth, design system, WCAG), picks the framework + rendering profile, forks into specialists (a11y-audit, performance-profiler, epic-design). Invokes the cs-frontend-engineer agent with context fork.
argument-hint: "<problem or surface to review>"

/cs:frontend-review — Frontend engineering review

Use the `cs-frontend-engineer` agent (uses `context: fork`) to handle this inquiry:

**$ARGUMENTS**

Forcing-question library

Canonical source: `engineering-team/skills/senior-frontend/references/forcing_questions.md` (7 questions, one-per-turn, recommendation + canon citation per question).

1. Primary device + network (desktop-fiber / mobile-4G / low-end Android / corporate) 2. LCP target on primary device (milliseconds) 3. Server Components vs SPA vs SSR vs SSG 4. JS bundle budget per route (KB gzipped) 5. SEO-dependent or auth-walled 6. Design-system location (Figma + tokens / ad-hoc Tailwind / headless UI) 7. WCAG target (AA / AAA / best-effort) + accessibility owner

Routing protocol

1. **Walk the 7 forcing questions** in `engineering-team/skills/senior-frontend/references/forcing_questions.md`. One per turn. Recommend with cited canon. Track in `/tmp/frontend-grill-<date>.md`. 2. **Surface kill criteria** — e.g., "SEO-dependent + SPA-only" trips. STOP and resolve. 3. **Run the deterministic profile picker:**

   python engineering-team/skills/senior-frontend/scripts/frontend_decision_engine.py \
     --primary-device <mobile-4g|desktop-fiber|low-end-android|corporate-network> \
     --lcp-target-ms <N> --seo-dependent <true|false> \
     --auth-walled <true|false> --team-size <N>

4. **Surface the matched profile + runner-up tradeoff** (if within 15%). 5. **Fork into specialists** (one at a time, depth-first):

• `a11y-audit` for WCAG baseline (always)
• `performance-profiler` for CWV baseline + bundle audit
• `epic-design` only for `astro-or-static` marketing surfaces
• `apple-hig-expert` only for Apple-platform-native surfaces
• `dependency-auditor` before any major release
• `cs-karpathy-reviewer` before any commit

Output expectations (≤ 200-word digest)

• Matched profile + reason
• Three CWV targets (LCP, INP, CLS) at p75 on the primary device
• Per-route JS bundle budget in KB-gzip
• Named a11y owner
• List of specialists invoked + artifact paths
• Recommended next sub-skill

Anti-patterns

• ❌ Recommending Next App Router as a universal default. Device + SEO + auth decide rendering.
• ❌ Setting "fast" as a target. Pick a number in ms.
• ❌ Skipping `a11y-audit` on customer-facing surface.
• ❌ Reimplementing perf-profiling logic. Fork into `performance-profiler`.

Customization

Profiles live at `engineering-team/skills/senior-frontend/profiles/`. Four built-in: `next-app-router`, `remix-or-sveltekit`, `vite-spa`, `astro-or-static`. Copy one to `<your-org>.json` and adjust to add your org's defaults.

Related commands

• `/cs:fullstack-review` — full-stack lens (parent)
• `/cs:backend-review` — for API contract on the consumer side
• `/cs:engineer-grill` — cross-role 21-question grill
• `/karpathy-check` — Karpathy 4-principle review