seo-sxo

# 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 ` | Full SXO analysis (auto-detect keyword from page) | | `/seo sxo ` | Full SXO analysis for a specific keyword | | `/seo sxo wireframe ` | Generate IST/SOLL wireframe with concrete placeholders | | `/seo sxo personas ` | 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 - AI Overview presence and source types 4. Calculate SERP consensus: - Dominant page type (>60% = strong consensus, 40-60% = mixed, <40% = fragmented) - Content depth expectations (average word count tier) - Schema expectation (most common structured data types) - Media expectations (video required? images critical?) ### Step 3: Page-Type Mismatch Detection This is the core SXO insight. Compare target page type against SERP consensus. **Mismatch severity levels:** | Target Type | SERP Expects | Severity | Recommendation | |-------------|-------------|----------|----------------| | Blog Post | Product Pages | CRITICAL | Create dedicated product page | | Blog Post | Comparison | HIGH | Restructure as comparison with