4 Agent Skills for Backend Engineers: Design Review, Zero-Downtime Migration, Production GenAI, Forecasting

Описание и применение

Автоматизированные чеклисты для проверки дизайна, миграции без простоя, готовности GenAI и прогнозирования в больших системах, повышающие надёжность и ускоряющие выпуск.

Задача

Backend teams need repeatable, automated reviews for design, migration, GenAI readiness, and forecasting to avoid incidents and downtime.

Результат

Automated, repeatable reviews that surface real incident failure modes, ensure zero‑downtime migration plans are reversible, validate GenAI production readiness, and catch forecasting pitfalls, leading to higher reliability and faster delivery.

Рабочий процесс

• Install the skills package via npx skills add shubhamkumbhalkar/skills on any agent (Claude Code, Codex, Cursor).
• Select the appropriate skill: distributed‑systems‑design‑review, zero‑downtime‑migration, genai‑production‑readiness, or time‑series‑forecasting‑review.
• Point the skill at the target artifact (design doc, PR, migration plan, or forecasting model).
• Let the agent run the checklist, generating a report with failure scenarios, blast radius, fixes, and a verdict (Ship / Ship‑with‑changes / Needs‑rework).
• Review the report, apply recommended fixes, and re‑run if necessary.
• Use the final verdict to decide whether to ship or iterate.
• Share findings with the team and iterate on the skill if gaps are found.

Доказательства

Point it at a design doc or PR and it reviews for the failure modes that cause real incidents: retries without idempotency, retry storms with no circuit breaker, missing backpressure, cross‑store write drift, hot partitions, and missing golden‑signal observability.

Источник

This skill produces a phased plan built on one rule: every phase is independently reversible. Expand (dual‑write), backfill (idempotent, reconciled), shadow‑verify against real traffic, incremental cutover (1/5/25/50/100%), then contract.

Источник

This skill checks the things a demo skips: an eval set with a regression gate, grounding and hallucination handling, prompt‑injection defense on untrusted input, a human‑in‑the‑loop boundary for consequential actions, cost/latency bounds and fallbacks, PII handling, and observability.

Источник

Forecasting is deceptively easy to get wrong: leakage and bad backtests inflate offline metrics, then quiet drift erodes them in production.

Источник