genpark-enterprise-spreadsheet-formula-dag-synthesizer-skill
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- License — License: MIT
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Enterprise Spreadsheet Financial Model & Formula DAG Synthesizer (inspired by Tencent WorkBuddy Goal-to-Excel Workflows). Synthesizes multi-tab financial models, detects circular references, compiles formula dependency DAGs (SUMIFS, XLOOKUP, CAGR, NPV), and evaluates deterministic preview cell matrices.
genpark-enterprise-spreadsheet-formula-dag-synthesizer-skill
Production-Grade Agentic Commerce & Enterprise Work Agent Skill • 100% Standard Library Python • Native Model Context Protocol (MCP)
🌟 Overview
genpark-enterprise-spreadsheet-formula-dag-synthesizer-skill delivers robust, industrial-grade capabilities engineered for Consumer Agentic Commerce (e.g. Meta Muse, Expedia, Mastercard Agent Connect) and Enterprise Workplace Execution (e.g. Tencent WorkBuddy Goal-to-PPT/Excel deliverable workflows). Built exclusively on the Python standard library with zero external runtime dependencies, it integrates seamlessly as a native Model Context Protocol (MCP) server or an importable Python module.
Enterprise Spreadsheet Financial Model & Formula DAG Synthesizer (inspired by Tencent WorkBuddy Goal-to-Excel Workflows). Synthesizes multi-tab financial models, detects circular references, compiles formula dependency DAGs (SUMIFS, XLOOKUP, CAGR, NPV), and evaluates deterministic preview cell matrices.
💡 Key Capabilities
- Zero-Dependency Architecture: Runs anywhere Python 3.9+ is installed without
pip installoverhead or supply-chain vulnerabilities. - Model Context Protocol (MCP) First: Compatible with Claude Desktop, Cursor, GenPark Engine, Meta Muse, and enterprise managed agent runtimes.
- Deterministic & Safe: Rigorous state machine models, cryptographic ledger hashes, mathematical dependency graphs, and full telemetry.
- High Concurrency & Low Latency: In-memory caching, topological cycle detection, and optimized execution loops.
🚀 Quickstart
1. Direct Python Usage
from client import EnterpriseSpreadsheetFormulaDAGSynthesizer
client = EnterpriseSpreadsheetFormulaDAGSynthesizer()
result = client.compile_spreadsheet_model()
print(result)
2. Standalone MCP Server Execution
Run the MCP server via standard JSON-RPC 2.0 stdio:
python mcp_server.py
Verify standard compliance and self-tests:
python mcp_server.py --test
3. Claude Desktop / Cursor MCP Configuration
Add this tool to your claude_desktop_config.json or Cursor MCP settings:
{
"mcpServers": {
"genpark-enterprise-spreadsheet-formula-dag-synthesizer-skill": {
"command": "python",
"args": ["/absolute/path/to/genpark-enterprise-spreadsheet-formula-dag-synthesizer-skill/mcp_server.py"]
}
}
}
🛠️ Verification & Testing
Run the included verification suite:
python example_usage.py
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
Developed with ❤️ by the GenPark Autonomous Agent Ecosystem Team.
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