Fähigkeiten performance-optimization
📦

performance-optimization

Inhaltsrevision r2 Sicher ⚡ Enthält Skripte⚙️ Externe Befehle📁 Dateisystemzugriff

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.

Unterstützt: Claude Codex Code(CC)
🥉 78 Bronze

Mit meinem Agent installieren

Kopieren Sie diese Anfrage in Ihren Agent. Sie enthält die maßgebliche Skill-Seite und das Manifest.

Agent-Anfrage
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.

Ihr Agent sollte weiterhin seinen Plan anzeigen und alle von der Sicherheitsrichtlinie verlangten Bestätigungen anfordern.

Agent-lesbare Ressourcen

Verwenden Sie diese Links, wenn ein KI-Agent, Crawler oder Skript sauberen Kontext benötigt, statt die vollständige Seite zu lesen.

Testen

„performance-optimization“ wird verwendet. The page has LCP of 4.2 seconds, a 1.8 MB JavaScript bundle, and large hero images.

Erwartetes Ergebnis:

  • 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“ wird verwendet. An API loads tasks and fetches each task owner separately.

Erwartetes Ergebnis:

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“ wird verwendet. A cache serves user profiles by profile ID, but the response includes tenant-specific permissions.

Erwartetes Ergebnis:

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

Sicherheitsaudit

Sicher
v2 • 19.9.2026 Versionsbericht öffnen

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.

1
Gescannte Dateien
497
Analysierte Zeilen
0
Prüfelemente
0
Falschmeldungen ignoriert
Das letzte abgeschlossene statische und semantische Audit erkannte keine bestätigten Sicherheitsbefunde. Dies beweist nicht, dass der Skill keine Nebenwirkungen hat.
Geprüft von: codex Audit-Verlauf anzeigen →
Diesen Bericht teilen & zitieren

Teile den versionierten Bewertungsbericht, das neutrale Badge, die Einbettungskarte und Zitate. Skillstore berichtet Nachweise, ohne zu entscheiden, ob dieser Skill sicher ist.

Versionsbericht öffnen
Sicherheitsbewertung

Berichtslink kopieren

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

Markdown-Badge

[![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-Badge

<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>

Einbettungskarte

<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>
Wissenschaftliche Zitate (APA · BibTeX · CFF)

APA-Zitat

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

BibTeX-Zitat

@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"

Varianten vergleichen

3 installierbare Varianten

Jeder Autor bleibt ein eigener installierbarer Skill. Die empfohlene Variante wird nach Skillstore-Nachweisen bewertet.

Warum diese Variante zuerst steht

Höhere Evidenzsicherheit
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ariegoldkin-performance-optimization

Skillstore-Score 78
Evidenzvertrauen Hoch
Skillstore-Nutzung 13
Aktualisiert

2026-09-09

addyosmani Aktuell

addyosmani-performance-optimization

Skillstore-Score 78
Evidenzvertrauen Mittel
Skillstore-Nutzung 1
Aktualisiert

2026-09-22

supercent-io-performance-optimization

Skillstore-Score 77
Evidenzvertrauen Hoch
Skillstore-Nutzung 23
Aktualisiert

2026-09-09

Skillstore-Score

Warum dieser Score Evidenzvertrauen: Mittel
55
Architektur
85
Wartbarkeit
87
Inhalt
65
Gemeinschaft
91
Spezifikationskonformität

Was Sie erstellen können

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.

Diese Prompts ausprobieren

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.

Bewährte Praktiken

  • 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.

Vermeiden

  • 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.

Häufig gestellte Fragen

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.

Entwicklerdetails

Lizenz

MIT

Skillstore-Revision

r2

Versionshinweis

Der Autor hat keine Version angegeben.

Ref.

5d5054f8a23586f9b500fece1cb613a9dffc787b

Aktualität der Wartung

19.9.2026

Nutzung

1 Downloads · 0 Aufrufe

Dateistruktur

📄 SKILL.md

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