Housing Calc Pro

• Develop a system for cross-linking new content within existing articles to improve SEO and user navigation, creating a robust internal linking structure.

• Objective: Enhance SEO by distributing link equity, improve user experience by guiding them to related content, and increase time on site.

• System Overview: A Python-based internal linking script (`internal_linker.py`) will be developed to:

- Scan New Articles: Automatically identify newly published articles.

- Analyze Content for Keywords: Extract key entities, topics, and keywords from the new article using NLP techniques.

- Identify Relevant Existing Articles: Search the existing article database for content that is semantically related to the new article's keywords and topics.

- Contextual Link Placement: For each new article, identify natural places within the text of existing articles where a link to the new article would be relevant and add value to the reader. Conversely, identify opportunities within the new article to link to older, related content.

- Anchor Text Optimization: Use descriptive and varied anchor text that accurately reflects the content of the linked-to article.

- Link Limit Enforcement: Implement a limit on the number of internal links added to an article to avoid over-optimization and maintain readability (e.g., 2-5 contextual links per 1000 words).

- Avoid Redundancy: Ensure that the same article is not linked multiple times from the same source article within close proximity.

• Workflow:

1. New Article Published: Trigger `internal_linker.py` after a new article goes live.

2. Keyword Extraction: The script extracts keywords from the new article.

3. Database Query: Queries a database/index of existing articles for relevant matches based on keywords and topics.

4. Suggest Link Placements: The script identifies optimal placement points and anchor text for both linking from existing articles to the new one, and from the new article to existing ones.

5. Automated Insertion: Using `edit_file` or `code_edit` functionality, the script inserts the new internal links into the respective articles.

6. Logging: Log all changes for review and rollback capability.

• Index of Articles: A simple JSON or database will store article titles, URLs, keywords, and a summary of their content to facilitate efficient searching for relevant links.

• Considerations:

- Content Management System (CMS) Integration: The script will need to interface with Housing Calc Pro's CMS (e.g., WordPress API, direct file modification for static sites) to read and update articles.

- Regular Re-evaluation: Periodically re-evaluate existing links to ensure accuracy and relevance as the content library grows.

• Output: A directory `internal_linking/` containing the `internal_linker.py` script, a `links_log.txt` to track all changes, and a conceptual `article_index.json` to store article metadata.