c24165b8bc
에이전트 8종(대화형/프로그래머 C·S/디자이너/설계자/기획자/QA/PD/PM)에게 [공통 기본 능력 + 롤별 Specialty] 2층으로 지식을 주입하기 위한 재분류. 문서 내용·포맷은 무수정, 폴더 이동만 (6,372개 문서 수 보존 확인). - Topic_Programming → Domain_Programming (내부 구조 보존) - Topic_Graphic → Domain_Design - Topic_Business → Domain_Product - Topic_General → Domain_General - _Common 신설: Math(구 Topic_Math_Specialty), Reasoning(구 General/From_Thinking & Reasoning), Reasoning_Creativity(구 General/From_창의성), Communication(Poetic_Blog_Writing + From_writing) - 타 도메인의 From_* 폴더는 유지 (출처 표기일 뿐, 이미 도메인에 맞게 분류된 문서) - 빈 폴더 정리 (memory/procedures) - 에이전트→폴더 매핑은 workspace의 .astra/agent-knowledge-map.json (9개 에이전트) Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
4.8 KiB
4.8 KiB
id, title, category, status, canonical_id, aliases, duplicate_of, source_trust_level, confidence_score, verification_status, tags, raw_sources, last_reinforced, github_commit, tech_stack
| id | title | category | status | canonical_id | aliases | duplicate_of | source_trust_level | confidence_score | verification_status | tags | raw_sources | last_reinforced | github_commit | tech_stack | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| wiki-2026-0508-time-to-interactive-tti | Time to Interactive (TTI) | 10_Wiki/Topics | verified | self |
|
none | A | 0.85 | applied |
|
2026-05-10 | pending |
|
Time to Interactive (TTI)
매 한 줄
"매 page가 user input에 reliably 반응할 수 있는 시점". 2018 Lighthouse에 도입된 TTI는 main thread quiet window를 측정. 2024년 INP (Interaction to Next Paint) 가 Core Web Vitals 의 official replacement 가 되었지만, TTI는 lab-time diagnostic 으로 여전히 유용.
매 핵심
매 정의 (Lighthouse algorithm)
- First Contentful Paint 이후 시작.
- 5-second quiet window: long task (>50ms) 가 없는 구간.
- network: 동시 in-flight request ≤ 2.
- 매 quiet window 의 시작 시점 = TTI.
매 vs other metrics
| Metric | Measures | Status (2026) |
|---|---|---|
| FCP | First Contentful Paint | active |
| LCP | Largest Contentful Paint | Core Web Vital |
| TTI | Main thread quiet | lab only |
| TBT | Total Blocking Time | lab proxy for TTI |
| INP | Interaction → Next Paint | Core Web Vital (2024+ replaces FID) |
매 왜 INP가 TTI를 대체했는가
- TTI 는 lab-only, single point — real user의 interaction 반영 X.
- INP 는 75th percentile of all interactions — full session 반영.
- TTI는 여전히 lab regression detection 에 유용.
매 응용
- CI performance budget (Lighthouse score).
- Pre-launch regression detection.
- JS bundle size impact 측정.
💻 패턴
Pattern 1: Lighthouse CLI 측정
npx lighthouse https://example.com \
--only-categories=performance \
--output=json \
--chrome-flags="--headless" \
--output-path=./report.json
jq '.audits["interactive"].numericValue' report.json
Pattern 2: Web Vitals JS (real user, INP)
import { onINP, onLCP, onCLS } from 'web-vitals/attribution';
onINP((metric) => {
navigator.sendBeacon('/analytics', JSON.stringify({
name: 'INP',
value: metric.value,
rating: metric.rating,
target: metric.attribution?.interactionTarget,
}));
});
Pattern 3: Reduce TTI — code splitting (React)
import { lazy, Suspense } from 'react';
const HeavyChart = lazy(() => import('./HeavyChart'));
export function Dashboard() {
return (
<Suspense fallback={<Skeleton />}>
<HeavyChart />
</Suspense>
);
}
Pattern 4: Defer non-critical scripts
<!-- Critical: render-blocking ok -->
<script src="/critical.js"></script>
<!-- Non-critical: defer until after parse -->
<script src="/analytics.js" defer></script>
<!-- Independent: async -->
<script src="/ads.js" async></script>
Pattern 5: Long task observer
const observer = new PerformanceObserver((list) => {
list.getEntries().forEach((entry) => {
if (entry.duration > 50) {
console.warn('Long task', entry.name, entry.duration);
// breakup with scheduler.yield() (2026 baseline)
}
});
});
observer.observe({ entryTypes: ['longtask'] });
Pattern 6: scheduler.yield (2026)
async function processItems(items) {
for (const item of items) {
process(item);
if (navigator.scheduling?.isInputPending()) {
await scheduler.yield(); // yield to user input
}
}
}
매 결정 기준
| 상황 | 매 metric |
|---|---|
| RUM (production users) | INP + LCP |
| Lab regression in CI | TTI / TBT |
| Initial render speed | FCP / LCP |
| Layout stability | CLS |
기본값: INP + LCP for RUM, TBT for lab CI gates.
🔗 Graph
- 부모: Web Performance · Core Web Vitals Optimization (INP, LCP, CLS)
- 변형: INP · LCP · TBT · FID
- 응용: Lighthouse · Code Splitting
- Adjacent: Service Worker · React Server Components — 경계 의식
🤖 LLM 활용
언제: lab performance regression, JS bundle audit, frontend optimization. 언제 X: production user-facing metric (use INP instead).
❌ 안티패턴
- TTI as RUM metric: TTI 는 lab-only. real user 측정에 사용 X.
- Optimizing for TTI alone: LCP / CLS / INP 의 무시.
- Synchronous third-party scripts: ads, analytics 의 sync 로딩 → TTI 폭발.
- Hydration-only SPA: massive JS bundle → bad TTI. Use SSR + Islands / RSC.
🧪 검증 / 중복
- Verified (web.dev/tti, Lighthouse v12, Chrome DevRel 2024 INP migration guide).
- 신뢰도 A.
🕓 Changelog
| 날짜 | 변경 |
|---|---|
| 2026-05-08 | Phase 1 |
| 2026-05-10 | Manual cleanup — TTI definition + INP migration context |