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search-strategy

Decompose natural language queries into source-specific searches across chat, knowledge bases, and project trackers.

4|2|Updated Mar 9, 2026
Search Tags:#information retrieval#search#ranking#enterprise search#query decomposition#multi-source search
One-click install
npx skills add https://github.com/kyopark2014/agent-plugins --skill search-strategy-kyopark2014
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: search-strategy
Source: https://github.com/kyopark2014/agent-plugins/tree/main/application/plugins/enterprise-search/skills/search-strategy
Command: npx skills add https://github.com/kyopark2014/agent-plugins --skill search-strategy-kyopark2014

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill transforms a single natural language question into targeted searches across multiple data sources, synthesizing the results into a single, ranked, and deduplicated answer.

Core Features & Use Cases

  • Query Decomposition: Breaks down complex questions into smaller, actionable sub-queries.
  • Source-Specific Translation: Generates queries tailored to the syntax of different data sources (e.g., chat, knowledge base, project tracker).
  • Result Ranking & Synthesis: Ranks results by relevance and combines them into a coherent response.
  • Use Case: Ask "What did we decide about the API migration timeline?" and get a consolidated answer derived from chat logs, documentation, and project updates.

Quick Start

Use the search-strategy skill to find out what was decided about the API migration timeline.

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 enterprise data sources using a single natural language query?▼

Multi-source enterprise search decomposes a single natural language query into source-specific operations, executing parallel searches across chat, knowledge bases, and project trackers to return comprehensive results.

How does query decomposition improve information retrieval from knowledge bases and chat logs?▼

Query decomposition breaks complex questions into smaller, actionable sub-queries tailored to the syntax of different data sources, enabling targeted searches and more accurate information retrieval from knowledge bases and chat logs.

Can I get ranked and deduplicated search results from project trackers and documentation?▼

Yes, enterprise search orchestration applies relevance scoring to results from project trackers and documentation, ranking and deduplicating the findings to synthesize a single coherent response.

What is the best way to orchestrate parallel searches across an internal knowledge base?▼

Intelligent search orchestration manages parallel execution across an internal knowledge base by translating natural language queries into source-specific syntax, applying fallback strategies to ensure comprehensive retrieval.

Does enterprise search support fallback strategies for missed results in project trackers?▼

Yes, enterprise search applies fallback strategies during multi-source retrieval to ensure comprehensive and accurate results even when initial queries against project trackers or chat logs yield insufficient data.

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