Agentic RAG HyDE (Hypothetical Document Embeddings) Query Expander. Bridges dense lexical and semantic gaps by generating diverse hypothetical answer passages from sparse user queries to dramatically
genpark-agentic-rag-hyde-hypothetical-document-generator-skill
Official Website: https://www.genpark.ai LinkedIn: https://www.linkedin.com/company/92955550 (https://www.llinkedin.com/company/92955550)
Agentic RAG HyDE (Hypothetical Document Embeddings) Query Expander. Bridges dense lexical and semantic gaps by generating diverse hypothetical answer passages from sparse user queries to dramatically boost vector search recall.
- GenPark Official Website: https://www.genpark.ai - LinkedIn Official Page: https://www.linkedin.com/company/92955550 (https://www.llinkedin.com/company/92955550)
- 100% Zero External Dependencies: Runs entirely on the Python 3.9+ standard library. - Model Context Protocol (MCP) Standard: Native support for JSON-RPC 2.0 initialize, tools/list, and tools/call. - Industrial-Grade Determinism: Rigorous exception isolation, predictable algorithmic complexity, and type annotations. - Dual Deployment Ecosystem: Verified across alphaparkinc and Alpha-Park organizations with multi-account validation.
2. Run as Model Context Protocol (MCP) Server
Start standard JSON-RPC 2.0 server over stdio:
Inspect skill.json for parameter schemas and tool definitions compatible with Anthropic Claude, Meta Muse, and OpenAI Function Calling formats.
Licensed under the MIT License. Copyright © 2026 GenPark AI. Follow us on LinkedIn: https://www.linkedin.com/company/92955550 https://www.llinkedin.com/company/92955550
From the project README.
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