\"algo-seo-technical\"
SkillSearchGives your AI the ability to diagnose and fix page speed problems so your site loads faster and ranks better in Google search. It focuses on Google's Core Web Vitals, the measurements behind Google's page experience signals: how quickly the main content appears, how fast the page reacts when someone clicks, and how much the layout shifts while loading. A vague request like 'my site is slow' is enough for it to get started.
Available today. Use it from your connected AI after setup.
No other account needed.
After adding it, describe the problem in your own words, such as 'my homepage is slow' or 'my page keeps shifting as it loads', and your AI will diagnose the page and work on improving it.
Then ask your AI: use the \"algo-seo-technical\" skill
What your AI can do with it
- Diagnose why a page feels slow
- Improve Largest Contentful Paint so the main content appears sooner
- Reduce layout shift so page elements stop jumping around while loading
- Improve how quickly the page responds when people interact with it
- Help pages pass Google's page experience signals
What this skill tells your AI
The instructions your AI receives, as published by charlieviettq/awesome-agent-skill in .claude/skills/algo-seo-technical/SKILL.md and read by ahel’s review.
Overview
Core Web Vitals are Google's page experience metrics: LCP (loading), INP (interactivity), and CLS (visual stability). Measured on real user data (CrUX). Pass thresholds: LCP < 2.5s, INP < 200ms, CLS < 0.1.
When to Use
Trigger conditions:
- Diagnosing why a site fails Core Web Vitals assessment
- Optimizing page load performance for SEO
- Reducing layout shift or improving interactivity
When NOT to use:
- When the issue is content relevance, not speed (use content SEO)
- When analyzing link authority (use PageRank / backlink analysis)
Algorithm
IRON LAW: CrUX Field Data Is the Source of Truth
Lab scores (Lighthouse) that pass can still FAIL in the field.
Google ranks based on REAL USER data (75th percentile):
- LCP < 2.5s (Good), 2.5-4.0s (Needs Improvement), > 4.0s (Poor)
- INP < 200ms (Good), 200-500ms (Needs Improvement), > 500ms (Poor)
- CLS < 0.1 (Good), 0.1-0.25 (Needs Improvement), > 0.25 (Poor)
Phase 1: Input Validation
Collect field data from CrUX API or Search Console. Run Lighthouse for lab baseline. Identify which metrics fail. Gate: Have both field and lab data; failing metrics identified.
Phase 2: Core Algorithm
LCP fixes: 1. Optimize largest element (hero image/text). 2. Preload critical resources. 3. Reduce server response time (TTFB). 4. Eliminate render-blocking resources.
INP fixes: 1. Break long tasks (> 50ms) into smaller chunks. 2. Reduce JavaScript execution time. 3. Use requestIdleCallback for non-critical work. 4. Minimize main thread blocking.
CLS fixes: 1. Set explicit dimensions on images/videos. 2. Reserve space for ads/embeds. 3. Avoid inserting content above existing content. 4. Use CSS contain for dynamic elements.
Phase 3: Verification
Re-run Lighthouse, deploy, then monitor CrUX for 28-day rolling average improvement. Gate: Lab scores pass; await field data confirmation (28-day cycle).
Phase 4: Output
Return audit results with specific fix recommendations prioritized by impact.
Output Format
{
"audit": {"lcp": {"value_ms": 3200, "status": "poor", "element": "hero-image.jpg", "fixes": ["preload", "compress"]}},
"metadata": {"url": "...", "data_source": "crux", "device": "mobile"}
}
Examples
Sample I/O
Input: URL with LCP=4.1s, CLS=0.32, INP=150ms Expected: LCP and CLS flagged as poor; INP passes. Fix priorities: CLS (image dimensions) → LCP (hero image preload)
Edge Cases
| Input | Expected | Why |
|---|---|---|
| SPA with client rendering | High LCP likely | No server-rendered content for LCP element |
| Page with ads | High CLS likely | Ad slots inject content dynamically |
| All metrics pass in lab | May still fail field | Real devices on slow networks differ from lab |
Gotchas
- Lab vs field gap: Lighthouse runs on a simulated fast device. Real users on 3G with old phones produce very different numbers.
- LCP element changes: The LCP element can differ across page loads (image vs text). Optimize for the MOST COMMON LCP element, not just one.
- CLS attribution: Layout shifts are blamed on the element that moved, but the CAUSE is often an element inserted above it. Trace the cause, not the symptom.
- INP replaced FID: As of March 2024, INP replaces FID. Old references to FID are outdated.
- 28-day lag: CrUX uses a 28-day rolling window. Fixes take up to a month to reflect in field data.
References
- For element-specific optimization techniques, see
references/optimization-techniques.md - For CrUX API usage and monitoring setup, see
references/crux-monitoring.md
Signals
- GitHub stars
- 26
- Forks
- 9
- Last commit
- Jul 2026
Advanced
- Catalog kind
- skill
- Gateway key
algo-seo-technical- Source
- github.com/charlieviettq/awesome-agent-skill