techwavedev SEO Fundamentals
Foundational principles for sustainable search visibility. This skill explains how search engines evaluate quality, not tactical shortcuts.
1. E-E-A-T (Quality Evaluation Framework)
E-E-A-T is not a direct ranking factor. It is a framework used by search engines to evaluate content quality, especially for sensitive or high-impact topics.
| Dimension | What It Represents | Common Signals |
|---|---|---|
| Experience | First-hand, real-world involvement | Original examples, lived experience, demonstrations |
| Expertise | Subject-matter competence | Credentials, depth, accuracy |
| Authoritativeness | Recognition by others | Mentions, citations, links |
| Trustworthiness | Reliability and safety | HTTPS, transparency, accuracy |
Pages competing in the same space are often differentiated by trust and experience, not keywords.
2. Core Web Vitals (Page Experience Signals)
Core Web Vitals measure how users experience a page, not whether it deserves to rank.
| Metric | Target | What It Reflects |
|---|---|---|
| LCP | < 2.5s | Loading performance |
| INP | < 200ms | Interactivity |
| CLS | < 0.1 | Visual stability |
Important context:
- CWV rarely override poor content
- They matter most when content quality is comparable
- Failing CWV can hold back otherwise good pages
3. Technical SEO Principles
Technical SEO ensures pages are accessible, understandable, and stable.
Crawl & Index Control
| Element | Purpose |
|---|---|
| XML sitemaps | Help discovery |
| robots.txt | Control crawl access |
| Canonical tags | Consolidate duplicates |
| HTTP status codes | Communicate page state |
| HTTPS | Security and trust |
Performance & Accessibility
| Factor | Why It Matters |
|---|---|
| Page speed | User satisfaction |
| Mobile-friendly design | Mobile-first indexing |
| Clean URLs | Crawl clarity |
| Semantic HTML | Accessibility & understanding |
4. Content SEO Principles
Page-Level Elements
| Element | Principle |
|---|---|
| Title tag | Clear topic + intent |
| Meta description | Click relevance, not ranking |
| H1 | Page’s primary subject |
| Headings | Logical structure |
| Alt text | Accessibility and context |
Content Quality Signals
| Dimension | What Search Engines Look For |
|---|---|
| Depth | Fully answers the query |
| Originality | Adds unique value |
| Accuracy | Factually correct |
| Clarity | Easy to understand |
| Usefulness | Satisfies intent |
5. Structured Data (Schema)
Structured data helps search engines understand meaning, not boost rankings directly.
| Type | Purpose |
|---|---|
| Article | Content classification |
| Organization | Entity identity |
| Person | Author information |
| FAQPage | Q&A clarity |
| Product | Commerce details |
| Review | Ratings context |
| BreadcrumbList | Site structure |
Schema enables eligibility for rich results but does not guarantee them.
6. AI-Assisted Content Principles
Search engines evaluate output quality, not authorship method.
Effective Use
- AI as a drafting or research assistant
- Human review for accuracy and clarity
- Original insights and synthesis
- Clear accountability
Risky Use
- Publishing unedited AI output
- Factual errors or hallucinations
- Thin or duplicated content
- Keyword-driven text with no value
7. Relative Importance of SEO Factors
There is no fixed ranking factor order. However, when competing pages are similar, importance tends to follow this pattern:
| Relative Weight | Factor |
|---|---|
| Highest | Content relevance & quality |
| High | Authority & trust signals |
| Medium | Page experience (CWV, UX) |
| Medium | Mobile optimization |
| Baseline | Technical accessibility |
Technical SEO enables ranking; content quality earns it.
8. Measurement & Evaluation
SEO fundamentals should be validated using multiple signals, not single metrics.
| Area | What to Observe |
|---|---|
| Visibility | Indexed pages, impressions |
| Engagement | Click-through, dwell time |
| Performance | CWV field data |
| Coverage | Indexing status |
| Authority | Mentions and links |
Key Principle: Sustainable SEO is built on useful content, technical clarity, and trust over time. There are no permanent shortcuts.
🧠 AGI Framework Integration
Adapted for @techwavedev/agi-agent-kit Original source: antigravity-awesome-skills
Hybrid Memory Integration (Qdrant + BM25)
Before executing complex tasks with this skill:
python3 execution/memory_manager.py auto --query "<task summary>"
Decision Tree:
- Cache hit? Use cached response directly — no need to re-process.
- Memory match? Inject
context_chunksinto your reasoning. - No match? Proceed normally, then store results:
python3 execution/memory_manager.py store \
--content "Description of what was decided/solved" \
--type decision \
--tags seo-fundamentals <relevant-tags>
Note: Storing automatically updates both Vector (Qdrant) and Keyword (BM25) indices.
Agent Team Collaboration
- Strategy: This skill communicates via the shared memory system.
- Orchestration: Invoked by
orchestratorvia intelligent routing. - Context Sharing: Always read previous agent outputs from memory before starting.
Local LLM Support
When available, use local Ollama models for embedding and lightweight inference:
- Embeddings:
nomic-embed-textvia Qdrant memory system - Lightweight analysis: Local models reduce API costs for repetitive patterns