Article SEO/LEO Enhancer

Analyze article content and add appropriate SEO/LEO frontmatter fields to improve search engine visibility and AI/LLM discoverability.

When to Use

• •User asks to optimize an article for SEO
• •User wants to add AI-friendly metadata to an article
• •User asks to enhance an article with structured data
• •Preparing an article for publication with full SEO/LEO optimization
• •User mentions adding FAQ schema, HowTo schema, or AI summary

Inputs

• •file_path: Path to the markdown article file
• •fields (optional): Specific fields to add (default: analyze and add all applicable)

Supported SEO/LEO Fields

Process

Step 1: Read and Analyze Article

1. •Read the markdown file
2. •Parse front matter (YAML between --- markers)
3. •Identify existing SEO/LEO fields (skip if already present)
4. •Analyze content structure:
   • •Headings hierarchy
   • •Presence of step-by-step instructions
   • •Q&A patterns
   • •Code examples
   • •Technical depth

Step 2: Determine Article-Type

Analyze content to select appropriate type:

Check for:

• •Title contains "How to", "Guide to", "Tutorial"
• •Numbered steps or ordered lists
• •Headings that are questions
• •<!-- faq-start --> or <!-- howto-start --> markers

Step 3: Determine Expertise-Level

Analyze based on:

Check for:

• •Prerequisite mentions
• •Complexity of code examples
• •Technical vocabulary density
• •Assumed knowledge references

Step 4: Generate AI-Summary

Create a 2-sentence summary optimized for AI citation:

Format:

AI-Summary: >
  [Sentence 1: What the article covers/teaches].
  [Sentence 2: Key insight, main takeaway, or unique value].

Guidelines:

• •First sentence: Factual statement of article scope
• •Second sentence: Key insight or actionable takeaway
• •Make it standalone (reader should understand value without reading article)
• •Avoid marketing language, be factual
• •Max 300 characters total

Example:

AI-Summary: >
  This article explains techniques to boost RAG pipeline performance
  in production environments. Key optimizations include hybrid search,
  re-ranking, and addressing the lost-in-the-middle problem.

Step 5: Extract Key-Takeaways

Identify 3-5 main points from the article:

Sources for takeaways:

• •Main section headings (## level)
• •Explicit conclusions or recommendations
• •TL;DR section if present
• •Summary paragraph

Format:

Key-Takeaways:
  - [Actionable insight 1]
  - [Actionable insight 2]
  - [Actionable insight 3]

Guidelines:

• •Start with action verbs when possible
• •Be specific, not generic
• •Each point should stand alone
• •Focus on what reader will learn/gain

Step 6: Extract FAQ (if applicable)

Trigger conditions:

• •Article has Q&A sections
• •Headings are questions (contain "?")
• •<!-- faq-start --> marker present
• •Article-Type is faq

Extract from:

1. •<!-- faq-start --> ... <!-- faq-end --> markers (priority)
2. •Headings that are questions + following paragraphs
3. •Explicit Q&A formatted sections

Format:

FAQ:
  - question: What is X?
    answer: >
      X is [concise answer, 1-3 sentences].
  - question: How do I Y?
    answer: >
      You can Y by [actionable steps].

Guidelines:

• •Keep answers concise (2-4 sentences ideal for featured snippets)
• •Answers should be self-contained
• •Extract 3-7 most relevant Q&A pairs
• •Escape special characters in YAML

Step 7: Extract HowTo-Steps (if applicable)

Trigger conditions:

• •Article-Type is howto
• •Contains numbered steps or ordered lists
• •<!-- howto-start --> marker present
• •Title contains "How to"

Extract from:

1. •<!-- howto-start --> ... <!-- howto-end --> markers (priority)
2. •Numbered headings (### Step 1:, ### 1., etc.)
3. •Ordered lists with substantial content

Format:

HowTo-Steps:
  - name: Step title without number prefix
    text: Brief description of what to do (1-2 sentences)
  - name: Next step
    text: Description

Guidelines:

• •Remove "Step N:" prefixes from names
• •Keep text concise (max 200 chars)
• •Include 3-10 steps
• •Steps should be actionable

Step 8: Add Topics (if beneficial)

When to add:

• •Tags are too generic (e.g., just "python", "ml")
• •Article covers specific subtopics not in tags
• •Semantic topics would help AI understanding

Format:

Topics:
  - specific-topic-1
  - specific-topic-2
  - specific-topic-3

Guidelines:

• •Use kebab-case
• •Be more specific than tags
• •3-5 topics maximum
• •Think: "What would someone search to find this?"

Step 9: Update Front Matter

Insert new fields in the front matter in this order (after existing fields):

---
Title: ...
Date: ...
Modified: ...
tags: ...
Category: ...
Image: ...
Summary: ...
Status: published

# SEO/LEO Enhancement
Article-Type: howto
Expertise-Level: intermediate
AI-Summary: >
  Two sentence summary here.
Key-Takeaways:
  - Point 1
  - Point 2
  - Point 3
Topics:
  - topic-1
  - topic-2
FAQ:
  - question: Q1?
    answer: A1
HowTo-Steps:
  - name: Step name
    text: Step description
---

Rules:

• •Add comment # SEO/LEO Enhancement before new fields
• •Only add fields that are applicable
• •Don't duplicate existing fields
• •Preserve all original front matter

Step 10: Invoke Post-Edit Actions

After completing SEO/LEO enhancement, invoke the article-post-edit-actions skill with:

• •file_path: Same article file
• •edit_descriptions: List of changes made, e.g.:
  • •"Added AI-Summary for LLM optimization"
  • •"Added Key-Takeaways (5 points)"
  • •"Added FAQ schema with 4 Q&A pairs"
  • •"Added HowTo-Steps (6 steps)"
  • •"Set Article-Type to howto"
  • •"Set Expertise-Level to intermediate"

Example Transformation

Before:

---
Title: Techniques to Boost RAG Performance in Production
Date: 2023-11-01
tags:
  - machine-learning
  - rag
  - llm
Category: Generative AI
Image: /images/head/boosting_RAG.jpg
Summary: This article discusses several advanced techniques...
Status: published
---

After:

---
Title: Techniques to Boost RAG Performance in Production
Date: 2023-11-01
Modified: 2026-02-07
tags:
  - machine-learning
  - rag
  - llm
Category: Generative AI
Image: /images/head/boosting_RAG.jpg
Summary: This article discusses several advanced techniques...
Status: published

# SEO/LEO Enhancement
Article-Type: article
Expertise-Level: intermediate
AI-Summary: >
  This article covers advanced techniques to optimize RAG pipeline 
  performance in production, including hybrid search, re-ranking, 
  and chunking strategies. Key insight: addressing the lost-in-the-middle 
  problem can significantly improve LLM output quality.
Key-Takeaways:
  - Combine semantic and keyword search with hybrid search for better retrieval
  - Use re-ranking to diversify retrieved snippets
  - Fine-tune embedding models for domain-specific improvements
  - Address lost-in-the-middle by reordering context snippets
  - Implement query transformations for complex queries
Topics:
  - retrieval-augmented-generation
  - vector-search-optimization
  - llm-context-management
  - embedding-fine-tuning
---

Output

• •Modified article with SEO/LEO frontmatter fields
• •Summary of added fields and their values
• •Post-edit actions invoked for metadata updates

Success Criteria

• • Article-Type correctly identified based on content
• • Expertise-Level appropriate for content complexity
• • AI-Summary is 2 sentences, factual, standalone
• • Key-Takeaways are specific and actionable (3-5 points)
• • FAQ extracted only when Q&A content exists
• • HowTo-Steps extracted only for tutorial/guide content
• • YAML formatting is valid (proper indentation, escaping)
• • Original front matter preserved
• • Post-edit actions skill invoked with change descriptions
• • Modified date updated

Edge Cases

Existing SEO/LEO Fields

• •Skip fields that already exist
• •Report which fields were skipped
• •Only add missing fields

No Clear Article-Type

• •Default to article
• •Note in output that type was defaulted

Short Articles

• •Still add Article-Type and Expertise-Level
• •AI-Summary may be very concise
• •Key-Takeaways may have only 2-3 points

Mixed Content (both FAQ and HowTo)

• •Can add both FAQ and HowTo-Steps
• •Article-Type should be primary focus (usually howto)

Special Characters in Content

• •Escape quotes in YAML: " → \"
• •Use > for multi-line strings
• •Avoid : at start of lines in values

Field Reference Quick Guide

# Always add:
Article-Type: article | howto | faq | tutorial
Expertise-Level: beginner | intermediate | advanced | expert
AI-Summary: >
  Two sentences. First states coverage, second gives key insight.

# Add for educational content:
Key-Takeaways:
  - Actionable point 1
  - Actionable point 2
  - Actionable point 3

# Add when tags are generic:
Topics:
  - specific-topic-1
  - specific-topic-2

# Add when Q&A content exists:
FAQ:
  - question: Question text?
    answer: Concise answer text.

# Add for tutorials/guides:
HowTo-Steps:
  - name: Step title
    text: Step description

Notes

• •This skill chains to article-post-edit-actions on completion
• •Focus on quality over quantity - only add applicable fields
• •AI-Summary is the most impactful field for LLM discoverability
• •Test generated YAML with a YAML validator if unsure
• •Reference: See pelican-themes/Flex/docs/SEO_LEO_CHEATSHEET.md for full field documentation