์Šคํ‚ฌ performance-optimization
๐Ÿ“ฆ

performance-optimization

์ฝ˜ํ…์ธ  ๋ฆฌ๋น„์ „ r2 ์•ˆ์ „ โšก ์Šคํฌ๋ฆฝํŠธ ํฌํ•จโš™๏ธ ์™ธ๋ถ€ ๋ช…๋ น์–ด๐Ÿ“ ํŒŒ์ผ ์‹œ์Šคํ…œ ์ ‘๊ทผ

Improve Application Performance with Evidence

Performance problems are difficult to diagnose when teams optimize from assumptions. This skill provides a measurement-first workflow for finding bottlenecks, testing fixes, and preventing regressions.

์ง€์›: Claude Codex Code(CC)
Maintain this Skill? Claim it ๐Ÿฅ‰ 78 ๋ธŒ๋ก ์ฆˆ

๋‚ด ์—์ด์ „ํŠธ๋กœ ์„ค์น˜

์ด ์š”์ฒญ์„ ์—์ด์ „ํŠธ์— ๋ณต์‚ฌํ•˜์„ธ์š”. ๊ณต์‹ Skill ํŽ˜์ด์ง€์™€ ๋งค๋‹ˆํŽ˜์ŠคํŠธ๊ฐ€ ํฌํ•จ๋˜์–ด ์žˆ์Šต๋‹ˆ๋‹ค.

์—์ด์ „ํŠธ ์š”์ฒญ
Review the Skillstore skill "performance-optimization" from https://skillstore.io/skills/addyosmani-performance-optimization.md and its manifest at https://skillstore.io/api/skills/addyosmani-performance-optimization/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

์—์ด์ „ํŠธ๋Š” ๊ณ„์†ํ•ด์„œ ๊ณ„ํš์„ ํ‘œ์‹œํ•˜๊ณ  ๋ณด์•ˆ ์ •์ฑ…์—์„œ ์š”๊ตฌํ•˜๋Š” ํ™•์ธ์„ ์š”์ฒญํ•ด์•ผ ํ•ฉ๋‹ˆ๋‹ค.

์—์ด์ „ํŠธ๊ฐ€ ์ฝ๊ธฐ ์‰ฌ์šด ๋ฆฌ์†Œ์Šค

AI ์—์ด์ „ํŠธ, ํฌ๋กค๋Ÿฌ, ์Šคํฌ๋ฆฝํŠธ๊ฐ€ ์ „์ฒด ํŽ˜์ด์ง€ ๋Œ€์‹  ์ •๋ฆฌ๋œ ์ปจํ…์ŠคํŠธ๋งŒ ํ•„์š”ํ•  ๋•Œ ์ด ๋งํฌ๋ฅผ ์‚ฌ์šฉํ•˜์„ธ์š”.

ํ…Œ์ŠคํŠธํ•ด ๋ณด๊ธฐ

"performance-optimization" ์‚ฌ์šฉ ์ค‘์ž…๋‹ˆ๋‹ค. The page has LCP of 4.2 seconds, a 1.8 MB JavaScript bundle, and large hero images.

์˜ˆ์ƒ ๊ฒฐ๊ณผ:

  • Prioritize the hero image and initial JavaScript payload.
  • Measure image transfer, render blocking, and bundle composition.
  • Test responsive image formats and route-level code splitting.
  • Keep the change only if LCP improves beyond normal run-to-run variance.

"performance-optimization" ์‚ฌ์šฉ ์ค‘์ž…๋‹ˆ๋‹ค. An API loads tasks and fetches each task owner separately.

์˜ˆ์ƒ ๊ฒฐ๊ณผ:

This is an N+1 query pattern. Fetch tasks with their owners in one query, then compare query count and p95 latency before and after.

"performance-optimization" ์‚ฌ์šฉ ์ค‘์ž…๋‹ˆ๋‹ค. A cache serves user profiles by profile ID, but the response includes tenant-specific permissions.

์˜ˆ์ƒ ๊ฒฐ๊ณผ:

The cache key omits a response input. Include tenant and permission context, or avoid shared caching when authorization data must remain isolated.

๋ณด์•ˆ ๊ฐ์‚ฌ

์•ˆ์ „

All 55 static findings were reviewed against SKILL.md. They are false positives caused by documentation examples, Markdown syntax, a relative reference link, and fixed diagnostic SQL; no malicious behavior or prompt injection was found.

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์Šค์บ”๋œ ํŒŒ์ผ
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๋ถ„์„๋œ ์ค„ ์ˆ˜
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๊ฒ€ํ†  ํ•ญ๋ชฉ
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์˜คํƒ ๋ฌด์‹œ๋จ
๊ฐ€์žฅ ์ตœ๊ทผ์— ์™„๋ฃŒ๋œ ์ •์ ยท์˜๋ฏธ๋ก ์  ๊ฐ์‚ฌ์—์„œ ํ™•์ธ๋œ ๋ณด์•ˆ ๋ฐœ๊ฒฌ ์‚ฌํ•ญ์ด ๊ฐ์ง€๋˜์ง€ ์•Š์•˜์Šต๋‹ˆ๋‹ค. ์ด๋Š” ์Šคํ‚ฌ์— ๋ถ€์ž‘์šฉ์ด ์—†์Œ์„ ์ฆ๋ช…ํ•˜์ง€ ์•Š์Šต๋‹ˆ๋‹ค.
์ด ๋ณด๊ณ ์„œ ๊ณต์œ  ๋ฐ ์ธ์šฉ

๋ฒ„์ „์ด ์ง€์ •๋œ ํ‰๊ฐ€ ๋ณด๊ณ ์„œ, ์ค‘๋ฆฝ ๋ฐฐ์ง€, ์ž„๋ฒ ๋“œ ์นด๋“œ ๋ฐ ์ธ์šฉ์„ ๊ณต์œ ํ•˜์„ธ์š”. Skillstore๋Š” ๊ทผ๊ฑฐ๋ฅผ ๋ณด๊ณ ํ•˜์ง€๋งŒ ์ด Skill์˜ ์•ˆ์ „ ์—ฌ๋ถ€๋ฅผ ํŒ๋‹จํ•˜์ง€ ์•Š์Šต๋‹ˆ๋‹ค.

๋ฒ„์ „๋ณ„ ๋ณด๊ณ ์„œ ์—ด๊ธฐ
๋ณด์•ˆ ํ‰๊ฐ€

๋ณด๊ณ ์„œ ๋งํฌ ๋ณต์‚ฌ

https://skillstore.io/skills/addyosmani-performance-optimization/audits/2?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

Markdown ๋ฐฐ์ง€

[![Skillstore security assessment](https://skillstore.io/badges/skills/addyosmani-performance-optimization/security.svg)](https://skillstore.io/skills/addyosmani-performance-optimization?utm_source=security_passport_badge)

HTML ๋ฐฐ์ง€

<a href="https://skillstore.io/skills/addyosmani-performance-optimization?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/addyosmani-performance-optimization/security.svg" alt="Skillstore security assessment" loading="lazy"></a>

์ž„๋ฒ ๋“œ ์นด๋“œ

<iframe src="https://skillstore.io/embed/skills/addyosmani-performance-optimization.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>
ํ•™์ˆ  ์ธ์šฉ (APA ยท BibTeX ยท CFF)

APA ์ธ์šฉ

addyosmani. (2026). performance-optimization security audit report (audit version 2) [Author version unspecified]. Skillstore. https://skillstore.io/skills/addyosmani-performance-optimization/audits/2

BibTeX ์ธ์šฉ

@techreport{addyosmani-addyosmani-performance-optimization-2026, author = {addyosmani}, title = {performance-optimization security audit report (audit version 2)}, institution = {Skillstore}, year = {2026}, number = {2}, url = {https://skillstore.io/skills/addyosmani-performance-optimization/audits/2}, note = {Author version unspecified} }

CITATION.cff

cff-version: 1.2.0 message: "If you use this Skill, cite its author and this versioned security audit report." title: "performance-optimization security audit report (audit version 2)" version: "unspecified" type: report authors: - name: "addyosmani" date-released: "2026-09-19" url: "https://skillstore.io/skills/addyosmani-performance-optimization/audits/2" identifiers: - type: other value: "skillstore:addyosmani-performance-optimization:audit:2" description: "Skillstore immutable audit report identifier"

๋ณ€ํ˜• ๋น„๊ต

์„ค์น˜ ๊ฐ€๋Šฅํ•œ ๋ณ€ํ˜• 3๊ฐœ

๊ฐ ์ž‘์„ฑ์ž์˜ ์Šคํ‚ฌ์€ ๋ณ„๋„์˜ ์„ค์น˜ ํ•ญ๋ชฉ์œผ๋กœ ์œ ์ง€๋ฉ๋‹ˆ๋‹ค. ์ถ”์ฒœ ๋ณ€ํ˜•์€ Skillstore ๊ทผ๊ฑฐ๋กœ ์ˆœ์œ„๊ฐ€ ์ •ํ•ด์ง‘๋‹ˆ๋‹ค.

์ด ๋ณ€ํ˜•์ด 1์œ„์ธ ์ด์œ 

๊ทผ๊ฑฐ ์‹ ๋ขฐ๋„๊ฐ€ ๋” ๋†’์Œ
ArieGoldkin ๊ถŒ์žฅ

ariegoldkin-performance-optimization

Skillstore ์ ์ˆ˜ 78
์ฆ๊ฑฐ ์‹ ๋ขฐ๋„ ๋†’์Œ
Skillstore ์‚ฌ์šฉ๋Ÿ‰ 20
์—…๋ฐ์ดํŠธ๋จ

2026-10-24

addyosmani ํ˜„์žฌ

addyosmani-performance-optimization

Skillstore ์ ์ˆ˜ 78
์ฆ๊ฑฐ ์‹ ๋ขฐ๋„ ์ค‘๊ฐ„
Skillstore ์‚ฌ์šฉ๋Ÿ‰ 6
์—…๋ฐ์ดํŠธ๋จ

2026-09-22

supercent-io-performance-optimization

Skillstore ์ ์ˆ˜ 77
์ฆ๊ฑฐ ์‹ ๋ขฐ๋„ ๋†’์Œ
Skillstore ์‚ฌ์šฉ๋Ÿ‰ 29
์—…๋ฐ์ดํŠธ๋จ

2026-09-09

Skillstore ์ ์ˆ˜

์ด ์ ์ˆ˜์˜ ์ด์œ  ์ฆ๊ฑฐ ์‹ ๋ขฐ๋„: ์ค‘๊ฐ„
55
์•„ํ‚คํ…์ฒ˜
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์œ ์ง€๋ณด์ˆ˜์„ฑ
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์ฝ˜ํ…์ธ 
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์ปค๋ฎค๋‹ˆํ‹ฐ
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์‚ฌ์–‘ ์ค€์ˆ˜

๋งŒ๋“ค ์ˆ˜ ์žˆ๋Š” ๊ฒƒ

Diagnose a Slow Web Page

Use measured browser data to identify bundle, rendering, image, interaction, or server-response bottlenecks.

Tune Database-Backed APIs

Review query plans, indexes, pagination, N+1 patterns, and connection pools before changing backend code.

Set a Regression Guardrail

Create performance budgets and monitoring checks that verify improvements and catch later regressions.

์ด ํ”„๋กฌํ”„ํŠธ๋ฅผ ์‚ฌ์šฉํ•ด ๋ณด์„ธ์š”

Find the First Measurement
My application feels slow. Ask for the minimum data needed, then identify the first measurements I should collect.
Review Frontend Metrics
Review these LCP, INP, CLS, bundle, and network results. Identify the most likely bottleneck and propose one testable fix.
Analyze a Query Plan
Analyze this query and EXPLAIN ANALYZE output. Explain the bottleneck, evaluate index options, and state the measurement needed after the change.
Design a Performance Experiment
Design a controlled performance experiment for this suspected bottleneck. Define the baseline, one change, success threshold, variance check, rollback rule, and regression guard.

๋ชจ๋ฒ” ์‚ฌ๋ก€

  • Measure a representative baseline before proposing an optimization.
  • Change one variable at a time and compare results against run-to-run variance.
  • Keep only changes that improve the target metric without reducing correctness.

ํ”ผํ•˜๊ธฐ

  • Adding indexes, caches, or memoization without evidence of a measured bottleneck.
  • Keeping a neutral optimization because it has already been implemented.
  • Combining several changes in one experiment so their effects cannot be attributed.

์ž์ฃผ ๋ฌป๋Š” ์งˆ๋ฌธ

What should I measure first?
Start with the user-visible symptom and collect a baseline for the relevant metric, such as LCP, INP, p95 latency, or query time.
Can this skill optimize my code automatically?
No. It provides analysis, recommendations, and verification steps. You decide which code, database, or infrastructure changes to implement.
When should I add a database index?
Inspect the query plan first. Add an index when it addresses the query shape and measure both read improvement and write cost.
How should I choose a cache?
Choose the smallest suitable layer based on scope, freshness, invalidation, and recomputation cost. Include every response input in the cache key.
How do I know an optimization worked?
Repeat the baseline measurement under comparable conditions. Keep the change only when the improvement exceeds normal variance and tests remain correct.
Does this cover production monitoring?
Yes. It recommends synthetic budgets and field monitoring for the primary user-facing metric, with alerts that lead back to fresh measurement.

๊ฐœ๋ฐœ์ž ์„ธ๋ถ€ ์ •๋ณด

์ž‘์„ฑ์ž

addyosmani

๋ผ์ด์„ ์Šค

MIT

Skillstore ๋ฆฌ๋น„์ „

r2

๋ฒ„์ „ ์•ˆ๋‚ด

์ž‘์„ฑ์ž๊ฐ€ ๋ฒ„์ „์„ ์„ ์–ธํ•˜์ง€ ์•Š์•˜์Šต๋‹ˆ๋‹ค.

์ฐธ์กฐ

5d5054f8a23586f9b500fece1cb613a9dffc787b

์œ ์ง€๋ณด์ˆ˜ ์ตœ์‹ ์„ฑ

2026. 9. 19.

์‚ฌ์šฉ๋Ÿ‰

1 ๋‹ค์šด๋กœ๋“œ ยท 0 ์กฐํšŒ

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