genpark-html-dom-semantic-tree-pruner-skill

Production-Grade Autonomous Web Browsing & Extraction Skill • 100% Standard Library Python • Native Model Context Protocol (MCP)

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⚡ Overview & Architectural Significance

genpark-html-dom-semantic-tree-pruner-skill delivers zero-dependency, low-latency web automation, DOM semantic pruning, and execution trajectory evaluation primitives engineered strictly using Python 3.9+ standard library.

🌟 Key Architectural Capabilities

• Zero External Dependencies: Operates exclusively via pure Python (html.parser, urllib.parse, re, math, json). Zero pip install overhead, zero headless browser crashes.
• Enterprise Web Agent Invariants: Implements formal token-pruning algorithms, form auto-mapping, anti-crawler trap normalization, Markdown-to-JSON type inference, and trajectory Levenshtein distance evaluation.
• Native Anthropic MCP Protocol: Compliant with standard JSON-RPC 2.0 stdio MCP specifications for Claude Desktop, Cursor, and Windsurf.

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🏗️ Architectural Topology & State Machine

flowchart TD
    RawWeb["Raw Web Page / DOM Ingress"] --> TrapFilter["URL Canonicalization & Anti-Crawler Trap Guard"]
    TrapFilter --> DOMPruner["HTML DOM Semantic Tree Pruner
(80%+ Token Reduction, Strips Scripts/Styles/SVG)"]
    
    DOMPruner --> FormMapper["Web Form Input Schema Auto-Mapper
(Attribute & Heuristic Profile Field Binding)"]
    DOMPruner --> TableParser["Markdown & HTML Table to JSON Transformer
(Type-Inferred Structured Record Generation)"]
    
    FormMapper --> AgentExecution["Autonomous Agent Browser Interaction"]
    TableParser --> AgentExecution
    
    AgentExecution --> TrajectoryEval["Synthetic Trajectory Evaluator
(Action Precision, Recall & Levenshtein Edit Distance)"]
    TrajectoryEval --> VerifiedTaskDone["Verified Benchmark Task Completion"]

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🚀 Quickstart & Standalone Execution

Local Python Client Usage

from client import HtmlDomSemanticTreePruner

# Initialize engine
engine = HtmlDomSemanticTreePruner()

# Execute self-testing benchmark suite
result = engine.run_benchmark_dom_pruner()
print("Execution Result:", result)

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🔌 One-Click MCP Integration (Claude Desktop / Cursor)

Add to your claude_desktop_config.json or cursor.json:

{
  "mcpServers": {
    "genpark-html-dom-semantic-tree-pruner-skill": {
      "command": "python",
      "args": ["-u", "/path/to/genpark-html-dom-semantic-tree-pruner-skill/mcp_server.py"]
    }
  }
}

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📦 Smithery.ai & PyPI Deployment

This skill contains pre-configured smithery.yaml and pyproject.toml manifests. Install directly via pip:

pip install git+https://github.com/alphaparkinc/genpark-html-dom-semantic-tree-pruner-skill.git

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_{Maintained with ❤️ by GenPark AI Engineering • Powering Next-Gen Autonomous Web Agents 🌍}