Analyze/Examine/Extract Elements from a Web Page's HTML/CSS/JS Source Code

I'd like to be able to Analyze/Examine/Extract Elements from a Web Page's HTML/CSS/JS source code, so that it enables me to ask AI Blaze about the code used on a web page.

A Web Page Source Explorer could add a powerful feature if we were able to ask questions about a web page's HTML/CSS/JS directly in AI Blaze. Users could then select any live page or paste its source, then ask questions or issue commands—“show me all variants on this page,” “extract inline styles,” or “explain this script block.”, or "extract all elements in a dropdown select box". Under the hood, Blaze would parse the DOM tree and stylesheet rules, tokenizes JavaScript, and feeds annotated snippets into its LLM.

This would make a sophisticated front-end analysis tool that if accessible via simple text prompts, would accelerate debugging, content auditing, accessibility reviews, and development documentation.

Feature Overview

Interactive Element Querying

  • Tag-level extraction: Ask for all instances of any tag or selector (e.g. elements, .cta-button classes).
  • Attribute filtering: Narrow queries by attributes (e.g. data- attributes, ARIA properties).
  • Hierarchy navigation: “Show me parent elements of this form field,” or “list siblings of this list item.”
  • Extract Form Elements with their respective options: Ask for all of the form elements on a web page.

Style & Layout Analysis:

  • CSS rule mapping: Extract computed style for any element, identify which stylesheet rule applies.
  • Inline vs. external: Highlight differences between inline styles and external rules.
  • Box-model breakdown: Report margins, padding, borders for quick debugging.

Script & Behavior Inspection:

  • Script block summarization: Ask “what does this function do?” on any inline or linked JS.
  • Event handler listing: List all listeners attached to a given element.
  • Dependency tracing: Trace imports or module dependencies for complex codebases.

Technical Approach;

Source Ingestion:

  • Enable AI Blazr to Examine source code pages & run AI Blaze queries on it: Visit any web page and run an AI Blaze query on the source code and Blaze retrieves the raw HTML/CSS/JS from a web page's source code, & then runs the AI Blaze prompt on it.

### Parsing & Tokenization:

  • DOM parser: Maybe convert the raw HTML into a structured tree, preserving line numbers.
  • CSSOM reader: Builds a CSS object model to resolve selectors and specificity.
  • JS static analysis: Tokenizes scripts and extracts function definitions, imports, and comments.

AI Blaze Integration:

  • Annotated context windows: For each user question, Blaze selects the minimal relevant AST (abstract syntax tree) nodes, serializes them, and includes them in the prompt.
  • Chain-of-thought prompts: Leverages step-by-step reasoning templates to explain complex behaviors or style cascades.

UI & UX Considerations

Prompt Interface

  • Integrated sidebar: Shows parsed tree view; click any node to auto-fill the prompt in a side bar.
  • Syntax highlighting: Displays returned snippets with color-coded tags, attributes, and code.

Response Presentation

  • Tabbed output: Separate HTML, CSS, and JS insights into tabs for focused reading.
  • Inline annotations: Hover over a line in the response to see original source context.

Benefits & Use Cases

Developer Productivity

  • Rapidly pinpoint style clashes or unwanted inheritance without switching tools.
  • Document page structure for hand-off by extracting clean, structured snippets.

Content & QA Audits

  • Verify accessibility attributes across large pages in seconds.
  • Extract all external script URLs to audit security or performance.

Training & Onboarding

  • New team members can query “what does this carousel component look like” and get both code and explanation.
  • Generates live samples and commentary for internal documentation.

A web page source code explorer feature would empower front-end developers to quickly analyze, extract, and question any element of a site’s front-end codebase directly in AI Blaze—turning raw source into actionable insight.