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optimization-mastery

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.

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xenitV1/claude-code-maestro
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الإنجليزية
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SKILL.md
تعليمات المصدر · معاينة للقراءة فقط
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. 1. **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`. 2. **Hydration Strategies:** * **Mandatory:** Use **Partial Hydration** or **Resumability** (e.g. Qwik/Astro patterns). * **Forbidden:** Massive "Full Hydration" of static content. 3. **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. 1. **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%. 2. **Query Budget:** * **Max Latency:** Sub-100ms for OLTP queries. * **Action:** Every index MUST be a "Covering Index" for critical read paths. 3. **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. 1. **Context Window Management:** * **Action:** Use "Context Folding" (summarizing history) to keep prompts under 4k tokens if possible. 2. **Credit-Based Execution:** * Assign a "Token Budget" to complex tool calling phases. 3. **Caching:** * Implement Semantic Caching for repetitive LLM queries. </ai_token_stewardship> <audit_and_reference> ## 📂 COGNITIVE AUDIT CYCLE 1. Is INP < 200ms? 2. Are primary keys UUIDv7? 3. Is hydration partial/resumable? 4. Is the token budget justified for this request? </audit_and_reference>
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