Habilidades performance-optimization
📦

performance-optimization

Revisión del contenido r1 Seguro Contiene scripts⚙️ Comandos externos📁 Acceso al sistema de archivos

Optimize Application Performance with Evidence

Performance changes often add complexity without proving user impact. This skill guides measurement, focused fixes, verification, and regression protection across application layers.

Compatible con: Claude Codex Code(CC)
🥉 77 Bronce

Instalar con mi Agente

Copia esta solicitud en tu Agente. Incluye la página canónica del Skill y el manifiesto.

Solicitud de agente
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.

Tu Agente debe seguir mostrando su plan y solicitar cualquier confirmación exigida por la política de seguridad.

Recursos legibles por agentes

Usa estos enlaces cuando un agente de IA, crawler o script necesite contexto limpio en vez de leer la página completa.

Pruébalo

Usando "performance-optimization". The product page has an LCP of 4.3 seconds on mobile. The hero image is 1.8 MB and begins loading late.

Resultado esperado:

  • Primary metric: mobile p75 LCP under 2.5 seconds.
  • Likely bottleneck: the oversized, late-discovered LCP image.
  • Experiment: resize responsive variants, use modern formats, and raise discovery priority.
  • Verification: repeat the same mobile test and confirm layout and image quality.

Usando "performance-optimization". An endpoint performs one task query and 80 owner queries. Its p95 latency is 920 milliseconds.

Resultado esperado:

  • Likely bottleneck: an N+1 query pattern.
  • Experiment: fetch owners through one join or batched query.
  • Success condition: fewer queries and a meaningful p95 reduction with unchanged results.
  • Regression control: add a query-count assertion for the endpoint.

Usando "performance-optimization". Memoization reduced average interaction latency by 3 percent, while repeated runs vary by 5 percent.

Resultado esperado:

Recommendation: revert. The observed change is smaller than normal variance, so the optimization has no demonstrated benefit.

Auditoría de seguridad

Seguro

All 55 static findings are false positives caused by Markdown syntax, fixed local import examples, and relative documentation links. The skill contains performance guidance and named tooling examples, with no prompt injection, arbitrary command construction, or filesystem operation.

1
Archivos escaneados
497
Líneas analizadas
0
Elementos de revisión
0
Falsos positivos ignorados
La auditoría estática y semántica completada más reciente no detectó hallazgos de seguridad confirmados. Esto no demuestra que el skill no tenga efectos secundarios.
Auditado por: codex
Compartir y citar este informe

Comparte el informe de evaluación versionado, la insignia neutral, la tarjeta insertable y las citas. Skillstore presenta evidencias sin decidir si este Skill es seguro.

Abrir el informe versionado
Evaluación de seguridad

Copiar enlace del informe

https://skillstore.io/skills/addyosmani-performance-optimization/audits/1?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

Insignia Markdown

[![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)

Insignia HTML

<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>

Tarjeta para insertar

<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>
Citas académicas (APA · BibTeX · CFF)

Cita APA

addyosmani. (2026). performance-optimization security audit report (audit version 1) [Author version unspecified]. Skillstore. https://skillstore.io/skills/addyosmani-performance-optimization/audits/1

Cita BibTeX

@techreport{addyosmani-addyosmani-performance-optimization-2026, author = {addyosmani}, title = {performance-optimization security audit report (audit version 1)}, institution = {Skillstore}, year = {2026}, number = {1}, url = {https://skillstore.io/skills/addyosmani-performance-optimization/audits/1}, 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 1)" version: "unspecified" type: report authors: - name: "addyosmani" date-released: "2026-09-13" url: "https://skillstore.io/skills/addyosmani-performance-optimization/audits/1" identifiers: - type: other value: "skillstore:addyosmani-performance-optimization:audit:1" description: "Skillstore immutable audit report identifier"

Comparar variantes

3 variantes instalables

Cada autor sigue siendo un skill instalable independiente. La variante recomendada se ordena según la evidencia de Skillstore.

Por qué esta variante es la primera

Mayor puntuación de Skillstore
ArieGoldkin Recomendado

ariegoldkin-performance-optimization

Puntuación de Skillstore 78
Confianza de la evidencia Alto
Uso en Skillstore 13
Actualizado

2026-09-09

supercent-io-performance-optimization

Puntuación de Skillstore 77
Confianza de la evidencia Alto
Uso en Skillstore 21
Actualizado

2026-09-09

addyosmani Actual

addyosmani-performance-optimization

Puntuación de Skillstore 77
Confianza de la evidencia Medio
Uso en Skillstore Desconocido
Actualizado

2026-09-14

Puntuación de Skillstore

Por qué esta puntuación Confianza de la evidencia: Medio
55
Arquitectura
85
Mantenibilidad
87
Contenido
65
Comunidad
83
Cumplimiento de la especificación

Lo que puedes crear

Improve Web Vitals

Diagnose poor LCP, INP, or CLS and prioritize measurable frontend changes.

Reduce API Latency

Trace slow endpoints through queries, connection pools, caching, and application code.

Prevent Regressions

Define budgets, repeatable benchmarks, CI gates, and production monitoring for critical user metrics.

Prueba estos prompts

Find the First Measurement
My application feels slow during [workflow]. Help me choose one user-facing metric, a representative test condition, and a repeatable baseline.
Diagnose a Bottleneck
Analyze these measurements and traces for [workflow]: [evidence]. Identify the likely bottleneck, explain the evidence, and propose the smallest useful experiment.
Review an Optimization
Review this proposed performance change: [change]. Compare baseline and result data, check correctness risks, account for variance, and recommend keep or revert.
Design Regression Controls
Create a performance protection plan for [system]. Define budgets, benchmark conditions, sample strategy, CI enforcement, field alerts, and an investigation workflow.

Mejores prácticas

  • Measure the same user-facing metric before and after each isolated change.
  • Validate performance gains only when functional tests remain green.
  • Record successful and reverted experiments with conditions and results.

Evitar

  • Do not optimize from intuition without profiling evidence.
  • Do not combine several changes into one measurement.
  • Do not keep complexity when improvement remains within measurement noise.

Preguntas frecuentes

Does this skill run profiling tools automatically?
No. It guides tool selection and analysis, but execution depends on the available environment and user approval.
Can it optimize frontend and backend systems?
Yes. It covers rendering, assets, bundles, APIs, queries, connection pools, and caching.
Which Core Web Vitals does it address?
It addresses LCP, INP, and CLS through measurement, diagnosis, focused changes, and monitoring.
Will every suggested optimization improve performance?
No. Each suggestion is a hypothesis that must exceed measurement variance and preserve correctness.
Does it support database tuning?
Yes. It covers query plans, N+1 patterns, pagination, indexes, selectivity, and connection pool sizing.
How does it prevent regressions?
It recommends repeatable budgets in CI and field monitoring for the user-facing metric.

Detalles del desarrollador

Licencia

MIT

Revisión de Skillstore

r1

Aviso de versión

El autor no declaró una versión.

Ref.

5526951beaeca22519572a471618555839b53b05

Actualidad del mantenimiento

14/9/2026

Uso

0 descargas · 0 vistas

Estructura de archivos

📄 SKILL.md

Más de addyosmani

Ver todo
Ver todo