bolt

仓库创建 2026年1月7日最近提交 2 天前SkillHot 收录 21 天前

▸ 精选理由

覆盖前后端的性能问题并带有参数化的自动调优流程，适合需持续优化的工程团队。

这个 Skill 做什么

自动诊断并优化前端重渲染与后端瓶颈，支持持续自动调优闭环。

定位并修复前端的重渲染、第三方脚本阻塞或 INP 问题，也会找出后端的 N+1、索引、缓存与连接池瓶颈。无论是一锤子提速还是想做持续自动调优（profile→调参→优化→验证）都能用，形成闭环优化。还会给出实操建议，如在 React 用 memo/懒加载、在后端用 DataLoader、索引或缓存策略等。

▸ 展开 SKILL.md 英文原文

Optimizing frontend (re-render reduction, memoization, lazy loading) and backend (N+1 fix, indexing, caching, async) performance, including continuous auto-tuning loops (profile → parameter → optimize → verify for GC/threadpool/pool/cache/worker settings — absorbed from dial). Use when one-shot speed improvement or continuous tuning is needed.

开发编程性能优化前端自动调优通用

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安装 / 使用

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帮我安装这个 skill：https://raw.githubusercontent.com/simota/agent-skills/main/bolt/SKILL.md

或 curl 直取 SKILL.md

curl -fsSL "https://raw.githubusercontent.com/simota/agent-skills/main/bolt/SKILL.md"

SKILL.MD 节选查看完整文件 ↗

<!--
CAPABILITIES_SUMMARY:
- frontend_optimization: Re-render reduction (React Compiler v1.0 auto-memo / manual memo for non-Compiler projects), lazy loading, virtualization, debounce/throttle, INP optimization (task breaking, main thread yield, third-party script audit), async waterfall detection and parallelization
- backend_optimization: N+1 fix (eager loading/DataLoader), connection pooling, async processing, compression, async waterfall elimination (sequential-to-parallel refactor)
- bundle_optimization: Route/component/library/feature-based code splitting, tree shaking, library replacement
- database_query_optimization: EXPLAIN ANALYZE metrics, index suggestion (B-tree/Partial/Covering

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