/cs-fullstack-review¶
Use the cs-fullstack-engineer agent (which uses context: fork to keep the parent thread clean) to handle this inquiry:
$ARGUMENTS
Forcing-question library¶
Canonical source: engineering-team/skills/senior-fullstack/references/forcing_questions.md (7 questions, one-per-turn, recommendation + canon citation per question).
- Team size now + 12-month headcount
- Deployment cadence (per-PR / daily / weekly / quarterly)
- Customer-facing / internal tool / marketing site
- One-year p50 + p99 traffic forecast
- Hiring-against vs training-into the stack
- Year-one monthly cloud + SaaS budget ceiling
- Three verifiable success criteria with numeric targets
Routing protocol¶
- Walk the 7 forcing questions in
engineering-team/skills/senior-fullstack/references/forcing_questions.md. One per turn. Recommend the answer with cited canon. Track in/tmp/fullstack-grill-<date>.md. - Surface kill criteria — if any question trips one (e.g., "microservices day 1, team size 3"), STOP and resolve before proceeding.
- Run the deterministic profile picker:
- Surface the matched profile + runner-up tradeoff (if within 15%).
- Fork into specialists (one at a time, depth-first):
api-design-reviewerfor API contractdatabase-designerfor schemaslo-architectfor reliability targetci-cd-pipeline-builderfor the pipelineperformance-profilerfor perf baselinecs-karpathy-reviewerbefore any commit
Output expectations (≤ 200-word digest)¶
- Matched profile + reason
- Three verifiable success criteria with numeric targets
- Named approver chain
- List of specialists invoked + artifact paths
- Recommended next sub-skill (if any)
Anti-patterns¶
- ❌ Bundling forcing questions — one per turn.
- ❌ Skipping the kill-criteria check.
- ❌ Reimplementing specialist scope. Fork — don't duplicate.
- ❌ Auto-approving production changes. Always name the human approver.
Customization¶
Profiles live at engineering-team/skills/senior-fullstack/profiles/. To customize for your org:
- Copy
saas-startup.json(or whichever best fits) to<your-org>.json. - Edit
constraints,stack_recommendations,success_thresholds,named_approver_chain. - The decision engine auto-discovers new profile JSONs.
Related commands¶
/cs:frontend-review— frontend-only deep dive/cs:backend-review— backend-only deep dive/cs:engineer-grill— cross-role 21-question forcing-question runner/karpathy-check— Karpathy 4-principle review before commit