SEO Sxo

Search Experience Optimization: reads Google SERPs backwards to detect page-type mismatches, derives user stories from search intent signals, and scores pages from multiple persona perspectives. Identifies why well-optimized pages fail to rank by analyzing what Google rewards for each keyword. Use when user says "SXO", "search experience", "page type mismatch", "SERP analysis", "user story", "persona scoring", "why isn't my page ranking", "intent mismatch", or "wireframe".

Business, Marketing & Sales|v1|Updated 7/2/2026|GitHub source

MCP get_skill({ skillId: "seo-sxo-5eabcbcb" })

Use this skill with your agent

Create a free account and connect via MCP

Get Started Free

# Search Experience Optimization (SXO)

SXO bridges the gap between SEO (what Google rewards) and UX (what users need).
Traditional SEO audits check technical health. SXO asks: "Does this page deserve
to rank for this keyword based on what Google is actually rewarding in the SERP?"

## Core Insight

A page can score 95/100 on technical SEO and still fail to rank because it is the
**wrong page type** for the keyword. If Google shows 8 product pages and 2 comparison
pages for your keyword, your blog post will never break through -- no matter how
well-optimized it is.

## Commands

| Command | Purpose |
|---------|---------|
| `/seo sxo <url>` | Full SXO analysis (auto-detect keyword from page) |
| `/seo sxo <url> <keyword>` | Full SXO analysis for a specific keyword |
| `/seo sxo wireframe <url>` | Generate IST/SOLL wireframe with concrete placeholders |
| `/seo sxo personas <url>` | Persona-only scoring (skip SERP analysis) |

## Execution Pipeline

### Step 1: Target Acquisition

1. Fetch the target URL via `scripts/render_page.py --mode auto` (SPA-aware and SSRF-safe)
2. Parse with `scripts/parse_html.py` to extract: title, H1, meta description,
   headings hierarchy, word count, schema markup, CTAs, media elements
3. If no keyword provided, extract primary keyword from title tag + H1 overlap
4. Validate keyword is non-empty before proceeding

### Step 2: SERP Backwards Analysis

Read `references/page-type-taxonomy.md` for classification rules.

1. Search Google for the target keyword (WebSearch)
2. For each of the top 10 organic results, record:
   - URL and domain authority tier (brand / niche authority / unknown)
   - Page type (classify using taxonomy)
   - Content format (long-form, listicle, how-to, comparison, tool, video)
   - Word count estimate (from snippet length and page structure)
   - Schema types present (from SERP features: ratings, FAQ, HowTo)
   - Media signals (video carousel, image pack, thumbnail presence)
3. Record SERP features present:
   - Featured snippet (paragraph / list / table / video)
   - People Also Ask (extract all visible questions)
   - Ads (top and bottom -- count and analyze ad copy themes)
   - Related searches (extract all)
   - Knowledge panel / local pack / shopping results

Continue reading

#work-life#productivity#seo#local-business#content#marketing#auditpython