Agent Skills › xenitV1/claude-code-maestro › optimization-mastery

optimization-mastery

GitHub

提供全栈性能优化指南，涵盖前端INP优化、部分水合及资源治理，后端UUIDv7索引与查询预算，以及AI Token成本控制，确保系统高效低延迟。

skills/optimization-mastery/SKILL.md xenitV1/claude-code-maestro

Trigger Scenarios

需要优化前端交互响应速度或降低包体积时设计数据库主键策略或优化高频查询性能时需要控制AI模型调用的Token消耗或上下文窗口时

Install

npx skills add xenitV1/claude-code-maestro --skill optimization-mastery -g -y

More Options

Use without installing

npx skills use xenitV1/claude-code-maestro@optimization-mastery

指定 Agent (Claude Code)

npx skills add xenitV1/claude-code-maestro --skill optimization-mastery -a claude-code -g -y

安装 repo 全部 skill

npx skills add xenitV1/claude-code-maestro --all -g -y

预览 repo 内 skill

npx skills add xenitV1/claude-code-maestro --list

SKILL.md

Frontmatter

{
    "name": "optimization-mastery",
    "description": "2026-grade Cross-Domain Optimization. Expertise in Interaction to Next Paint (INP), Partial Hydration, UUIDv7 indexing, and AI Token Stewardship. Performance is a feature, not an afterthought.",
    "allowed-tools": "Read, Write, Edit, Glob, Grep, Bash"
}

<domain_overview>

⚡ OPTIMIZATION MASTERY: THE VELOCITY CORE

Philosophy: Efficiency is the highest form of quality. Minimal overhead, maximum impact. Performance-First is the only law. INTERACTION HYGIENE MANDATE (CRITICAL): Never prioritize synthetic benchmarks over real-world interaction smoothness. AI-generated code often misses Interaction to Next Paint (INP) bottlenecks caused by synchronous main-thread blocking. You MUST use scheduler.yield() or requestAnimationFrame for any complex DOM or state updates triggered by user events. Any implementation that risks "Layout Thrashing" or exceeds the 200ms INP threshold must be rejected. </domain_overview> <frontend_velocity>

🎨 PROTOCOL 1: FRONTEND PRECISION (INP & BUNDLE)

Aesthetics must be fast. Refer to frontend-design for visuals, but enforce these for speed.

The INP Threshold:
- Core Metric: Interaction to Next Paint (INP) MUST be < 200ms.
- Action: Yield to main thread for heavy logic. Use scheduler.yield() or requestIdleCallback.
Hydration Strategies:
- Mandatory: Use Partial Hydration or Resumability (e.g. Qwik/Astro patterns).
- Forbidden: Massive "Full Hydration" of static content.
Asset Governance:
- Images: Modern formats (AVIF/WebP) with srcset are mandatory.
- Fonts: Only wght variable fonts; subsetted. </frontend_velocity> <backend_velocity>

🏗️ PROTOCOL 2: BACKEND VELOCITY (QUERY & DATA)

The backend must be a fortress of speed. Refer to backend-design for architecture.

Identifier Strategy:
- Mandatory: Use UUIDv7 for all primary keys in high-insert tables.
- Rationale: Time-sortable IDs prevent B-tree fragmentation and boost insert speed by ~30%.
Query Budget:
- Max Latency: Sub-100ms for OLTP queries.
- Action: Every index MUST be a "Covering Index" for critical read paths.
Edge compute:
- Offload logic to Edge Functions (Vercel/Cloudflare) to reduce Time-to-First-Byte (TTFB). </backend_velocity> <ai_token_stewardship>

🤖 PROTOCOL 3: AI TOKEN STEWARDSHIP (RESOURCE OPS)

AIs are expensive/slow. Optimize the "thought" itself.

Context Window Management:
- Action: Use "Context Folding" (summarizing history) to keep prompts under 4k tokens if possible.
Credit-Based Execution:
- Assign a "Token Budget" to complex tool calling phases.
Caching:
- Implement Semantic Caching for repetitive LLM queries. </ai_token_stewardship> <audit_and_reference>