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search-integration

Define search triggers, source priorities, and re-search rules for AI prompts.

154|38|Updated May 4, 2026
Search Tags:#search#retrieval#ai prompts#multi-query#knowledge sources#source-priority
One-click install
npx skills add https://github.com/kangarooking/system-prompt-skills --skill search-integration
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: search-integration
Source: https://github.com/kangarooking/system-prompt-skills/tree/main/search-integration
Command: npx skills add https://github.com/kangarooking/system-prompt-skills --skill search-integration

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

AI prompts often need guidance on when to search, what to search, and which data sources to query. This Skill provides a structured approach to define search triggers, sources, and re-search rules to ensure up-to-date and verifiable results.

Core Features & Use Cases

  • Search trigger matrix design: define when to search vs. skip search depending on content type and timeliness
  • Multi-query strategy: require diverse query shapes to cover intent
  • Source priority and fallback: establish enterprise data, licensed data, public sources with clear priority and downgrades
  • Re-search policy on follow-up questions: avoid stale results by re-running searches
  • Domain-specific search rules: finance, local, travel, sports etc.
  • Cost-awareness: treat search as cheap and justify latency allowances
  • No-search fallback: for notebooks and strict source-based reading, rely on citations

Quick Start

Define your initial search triggers, source priorities, and re-search rules to govern how your AI agent hunts for information.

Frequently Asked Questions about search-integration

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

FAQPage Schema
How do I control when an AI prompt triggers a real-time knowledge search?▼

Control AI search behavior by defining a search trigger matrix that specifies exactly when to search versus skip search based on content type and timeliness constraints.

What is a multi-query strategy for AI knowledge retrieval?▼

A multi-query strategy for knowledge retrieval requires generating diverse query shapes to comprehensively cover user intent, ensuring your AI agent captures relevant information across multiple data sources.

How do I prevent stale search results on follow-up questions in chatbots?▼

Prevent stale search results by applying a re-search policy that re-runs knowledge retrieval queries on follow-up questions, ensuring your chatbot always provides up-to-date answers.

Can I set domain-specific search rules for finance or travel AI assistants?▼

Yes, you can set domain-specific search rules for finance, local, travel, and sports contexts, applying tailored retrieval constraints and fallback handling to match specialized knowledge requirements.

When should I use a no-search fallback in an AI prompt?▼

Use a no-search fallback for notebooks and strict source-based reading tasks where your AI should rely entirely on provided citations rather than triggering external knowledge retrieval.

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