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.
Copy this request to your Agent. It includes the canonical Skill page and manifest.
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.Your Agent should still show its plan and request any confirmation required by the security policy.
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Using "performance-optimization". The page has LCP of 4.2 seconds, a 1.8 MB JavaScript bundle, and large hero images.
Expected outcome:
Using "performance-optimization". An API loads tasks and fetches each task owner separately.
Expected outcome:
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.
Using "performance-optimization". A cache serves user profiles by profile ID, but the response includes tenant-specific permissions.
Expected outcome:
The cache key omits a response input. Include tenant and permission context, or avoid shared caching when authorization data must remain isolated.
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.
Share the versioned assessment report, neutral badge, embed card, and citations. Skillstore reports evidence without deciding whether this Skill is safe.
https://skillstore.io/skills/addyosmani-performance-optimization/audits/2?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report[](https://skillstore.io/skills/addyosmani-performance-optimization?utm_source=security_passport_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><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>addyosmani. (2026). performance-optimization security audit report (audit version 2) [Author version unspecified]. Skillstore. https://skillstore.io/skills/addyosmani-performance-optimization/audits/2@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}
}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"
Each author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.
Why this variant is first
ariegoldkin-performance-optimization
2026-09-09
addyosmani-performance-optimization
2026-09-22
supercent-io-performance-optimization
2026-09-09
Use measured browser data to identify bundle, rendering, image, interaction, or server-response bottlenecks.
Review query plans, indexes, pagination, N+1 patterns, and connection pools before changing backend code.
Create performance budgets and monitoring checks that verify improvements and catch later regressions.
My application feels slow. Ask for the minimum data needed, then identify the first measurements I should collect.
Review these LCP, INP, CLS, bundle, and network results. Identify the most likely bottleneck and propose one testable fix.
Analyze this query and EXPLAIN ANALYZE output. Explain the bottleneck, evaluate index options, and state the measurement needed after the change.
Design a controlled performance experiment for this suspected bottleneck. Define the baseline, one change, success threshold, variance check, rollback rule, and regression guard.
Author
addyosmaniLicense
MIT
Skillstore revision
r2
Version notice
The author did not declare a version.
Ref
5d5054f8a23586f9b500fece1cb613a9dffc787b
Maintenance freshness
9/19/2026
Usage
1 downloads · 0 views
File structure
📄 SKILL.md
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