DarkzSEO

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│  Static Codebase Auditor for 2026 Search Standards             │
│  SEO · GEO · AIO · AEO — 16 Checks, Zero APIs, Pure Analysis   │
└─────────────────────────────────────────────────────────────────┘

A lightweight, local-only Python CLI for auditing HTML/JSX/Template files against 2026 Search Standards. No external APIs required.

Features

• 16 Automated Checks across 4 categories
• Zero API Dependencies - runs entirely offline
• Color-Coded Console Output for quick severity identification
• JSON Report Export for CI/CD integration
• Template Agnostic - works with HTML, JSX, Vue, Svelte, Astro, PHP, EJS, and more

Installation

pip install -r requirements.txt

Usage

# Basic scan
python darkzseo.py --path ./src

# With brand name (for entity salience check)
python darkzseo.py --path ./public --brand "MyCompany"

# Custom output file
python darkzseo.py --path ./templates --output results.json

# Quiet mode (summary only)
python darkzseo.py --path ./src --quiet

Audit Categories

🟢 SEO (Technical Health)

Check	What it Detects
Orphan Pages	Files that exist but are never linked to
Resource Hints	External scripts missing preconnect/dns-prefetch
CLS Risk	Images/videos/iframes missing width/height
Render Budget	@import rules and expensive * selectors

🟣 GEO (Generative Engine Optimization)

Check	What it Detects
Trust Network	Long content lacking authority links (.gov, .edu, etc.)
Entity Salience	Brand not in H1 or first 200 words
Data Density	Low table/list ratio on content pages
Freshness	Missing or stale dateModified

🔵 AIO (AI Overviews)

Check	What it Detects
Comparison Gap	"vs"/"best" in title without comparison table
Direct Answer	Question headers not followed by concise paragraphs
Video Schema	Video content missing VideoObject JSON-LD
Skimmability	Paragraphs exceeding 150 words

🔷 AEO (Answer Engine Optimization)

Check	What it Detects
Simplicity Score	Complex vocabulary (Flesch-Kincaid proxy)
QA Proximity	Elements interrupting question-answer flow
Speakable Schema	Missing Speakable markup on Q&A content
Unit Clarity	Bare units without <abbr> tags

Output

Console

Color-coded findings grouped by category and severity:

• 🔴 CRITICAL/HIGH - Must fix for search visibility
• 🟡 MEDIUM - Recommended improvements
• 🔵 LOW/INFO - Nice to have optimizations

JSON Report

{
  "generated_at": "2026-01-20T20:00:00",
  "files_scanned": 42,
  "total_findings": 15,
  "summary": {
    "CRITICAL": 0,
    "HIGH": 5,
    "MEDIUM": 7,
    "LOW": 3
  },
  "findings": [
    {
      "category": "SEO",
      "severity": "HIGH",
      "file": "index.html",
      "message": "CLS Risk: <img> missing width/height"
    }
  ]
}

CI/CD Integration

DarkzSEO returns exit code 1 if any HIGH or CRITICAL findings are detected, making it perfect for CI pipelines:

# GitHub Actions example
- name: SEO Audit
  run: python darkzseo.py --path ./public --quiet

License

MIT