search-strategy

Name: search-strategy
Availability: InStock
Author: hvkshetry

Decompose natural language queries into source-specific searches across household data sources.

15|7|Updated Aug 6, 2025

Search Tags:#information retrieval #multi-source #search #orchestration #natural language processing #query decomposition

Ready to run

npx skills add https://github.com/hvkshetry/StewardOS --skill search-strategy-hvkshetry

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: search-strategy
Source: https://github.com/hvkshetry/StewardOS/tree/main/skills/shared/search-strategy
Command: npx skills add https://github.com/hvkshetry/StewardOS --skill search-strategy-hvkshetry

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill transforms complex natural language questions into targeted, multi-source searches, synthesizing results into a single, coherent answer, eliminating the need for users to manually query disparate systems.

Core Features & Use Cases

Query Decomposition: Breaks down natural language questions into specific search components (keywords, entities, intent).
Multi-Source Orchestration: Generates and executes targeted queries across various household data sources (email, documents, finances, etc.).
Result Synthesis & Ranking: Ranks and deduplicates results from different sources to provide a unified, relevant answer.
Use Case: Ask "When is the property tax payment due for Maple Street?" and get a consolidated answer derived from your email, document storage, and financial records.

Quick Start

Use the search-strategy skill to find out when the property tax payment comes due for Maple Street.

Frequently Asked Questions about search-strategy

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

FAQPage Schema

How do I search across multiple household data sources like email and financial records at once?▼

Multi-source search orchestration decomposes natural language queries into source-specific syntax, executing targeted searches across email, documents, and financial records simultaneously. It ranks and deduplicates results to provide a single, coherent answer.

How does natural language query decomposition work for information retrieval?▼

Natural language query decomposition analyzes question types and extracts specific search components like keywords, entities, and intent. It translates these into source-specific syntax to generate parallel, ranked results from diverse data systems.

Can I use natural language processing to search documents and entity management systems together?▼

Yes, you can use natural language processing to orchestrate targeted searches across documents and entity management systems. It extracts search components from your query and generates parallel, ranked results for unified answers.

What is the best way to find specific information across disparate household data systems?▼

The best way to find information across disparate household data systems is using search orchestration. It transforms complex questions into targeted queries, synthesizes results from multiple sources, and ranks them for a unified answer.

Does multi-source search orchestration support querying financial records and email simultaneously?▼

Multi-source search orchestration supports querying financial records, email, and document storage simultaneously. It generates source-specific queries from your natural language input and synthesizes the results into a single ranked output.