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context-query-rewrite

Rewrite user queries with intent extraction, lane filters, and temporal windows.

Updated Aug 27, 2026
Search Tags:#semantic search#context engineering#query rewrite#intent extraction#retrieval optimization
One-click install
npx skills add https://github.com/OrionArchitekton/cosmocrat-core --skill context-query-rewrite
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: context-query-rewrite
Source: https://github.com/OrionArchitekton/cosmocrat-core/tree/main/skills/ops/context-query-rewrite
Command: npx skills add https://github.com/OrionArchitekton/cosmocrat-core --skill context-query-rewrite

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill addresses the challenge of imprecise user queries that lead to suboptimal search results by automatically refining them for better semantic understanding.

Core Features & Use Cases

  • Intent Extraction: Identifies the core purpose behind a user's natural language query.
  • Automated Filtering: Appends relevant lane and domain filters to narrow down search scope.
  • Temporal Inference: Determines whether a query requires recent or historical data.
  • Use Case: A user asks "show me recent performance metrics". The skill rewrites this to "performance metrics" with a time_window of 90 days and the appropriate lane filter, ensuring more accurate and relevant results.

Quick Start

Use the context query rewrite skill to refine the user query "what are the latest sales figures?".

Frequently Asked Questions about context-query-rewrite

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How does query rewrite improve semantic search accuracy?▼

Query rewrite improves semantic search accuracy by extracting user intent, adding domain filters, and inferring temporal windows to transform raw natural language input into structured, retrievable queries.

What is intent extraction in conversational AI retrieval?▼

Intent extraction in conversational AI retrieval identifies the core purpose behind a natural language query, enabling automated filtering to narrow down the search scope for more relevant results.

How do I add temporal windows and domain filters to user queries?▼

You add temporal windows and domain filters by applying natural language processing to infer historical or recent data requirements, appending lane filters to refine the search scope automatically.

When do I need context engineering for search systems?▼

You need context engineering for search systems when imprecise user queries lead to suboptimal results, requiring automated query refinement to achieve better semantic understanding and retrieval optimization.

Can I use query rewrite for natural language performance metrics requests?▼

Yes, you can use query rewrite for natural language performance metrics requests by transforming queries into structured terms with specific time windows and lane filters to ensure accurate retrieval.

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