Agent skill · Content & Marketing

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".

Infrasity-Labsgithub.com/Infrasity-LabsGitHub ↗
claude-codeMIT
Install
npx skills add Infrasity-Labs/dev-gtm-claude-skills --skill seo-sxo --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 5
SKILL.md size: 10 KB
Bundled scripts: none
Path: .claude/skills/seo-sxo/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 97
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# 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/fetch_page.py` (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.

What's inside
Steps it walks through
  1. Core Insight
  2. Commands
  3. Execution Pipeline
  4. Step 1: Target Acquisition
  5. Step 2: SERP Backwards Analysis
  6. Step 3: Page-Type Mismatch Detection
  7. Step 4: User Story Derivation
  8. Step 5: Gap Analysis
  9. Step 6: Persona-Based Scoring
  10. Step 7: Wireframe Generation (Optional)
  11. DataForSEO Integration
  12. SXO Score vs SEO Health Score
  13. Cross-Skill References
  14. Output Format
Ships with 4 files
  • references/page-type-taxonomy.md
  • references/persona-scoring.md
  • references/user-story-framework.md
  • references/wireframe-templates.md
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About this skill
What does the seo-sxo skill do?

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".

How do I install it?

Run `npx skills add Infrasity-Labs/dev-gtm-claude-skills --skill seo-sxo --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From Infrasity-Labs/dev-gtm-claude-skills, a repository with 97 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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