Enhanced reference retrieval through AI-powered search tools that provide more precise and contextual access to your uploaded documents
Agentic search is now on by default for every app that has references. There’s nothing to turn on: as soon as you add a reference, your app can search it.
The Agentic Search Tool transforms how your Playlab apps access and utilize uploaded reference materials. Instead of relying on the traditional reference system that finds only the 10 most similar snippets, this MCP-powered tool provides intelligent search capabilities that can navigate through your documents like an expert would, finding specific information with greater precision and context awareness.Think of it like having a knowledgeable research assistant who knows exactly where to look in your filing cabinet. Rather than randomly pulling out the first 10 files that seem related, this tool can systematically search through your organized materials until it finds exactly what’s needed for the conversation.
Because agentic search replaces the traditional snippet lookup, you’ll see the app’s searches as a knowledge search step in the conversation instead of the “references used” widget.
The current reference system works by reading your conversation and finding the 10 most similar snippets from your reference collection. While helpful, this approach has several limitations:Limited Scope: What if the answer isn’t in those 10 snippets?Shallow Search: What if you need information from multiple sections or documents?Scale Challenges: With a large number of references, finding the right information in one try becomes unlikelyManual Overhead: You need to carefully select references for each app
The Knowledge Graph Advantage
The Agentic Search Tool treats your uploaded documents as an organized knowledge system. Just like a well-organized teacher’s filing cabinet with clearly labeled folders and sections, the AI can:Navigate Systematically: Move through document structures logically to find relevant informationSearch Comprehensively: Continue searching until it has all needed information (up to system limits)Understand Context: Recognize relationships between different pieces of informationAccess Everything: Work with your entire reference collection rather than pre-selected subsets
Navigate to the References section in your Playlab builder interface by clicking the References icon.
2
Add your references
Click Add reference to app and upload files, add a URL, or browse libraries. Once a reference finishes processing, agentic search turns on automatically for your app. There are no toggles to set.
Agentic search uses two tools together: the References Search Tool finds specific information, and the List Session References Tool lists the references available to the app. Both switch on together.
3
Add to Your App's Instructions (optional)
For more control over how your app searches, you can add lines like these to your app’s Instructions:
You have access to enhanced reference search capabilities through MCP tools. When users ask questions that might be answered by uploaded documents, use the reference search tools to find specific, relevant information. The List Session References Tool helps identify available references, while the References Search Tool performs targeted searches within those documents.Continue searching until you have comprehensive information to answer the user's question. Always check tool outputs for detailed reference information and cite sources appropriately.
4
Optimize Your Document Organization
For best results, organize your reference materials with:
Descriptive file names: Use clear, specific names like “Grade-5-Math-Unit-3-Fractions-Teacher-Manual.pdf” instead of “Document1.pdf”
Well-structured documents: Files with clear headings and sections work best
5
Test Different Query Types
Validate the tools work correctly by testing various query categories to search your reference files.Multi-Step Research: “What are the prerequisites for teaching fractions, and what common misconceptions should I watch for?”
The primary search engine that queries your uploaded documents for specific information and content, continuing to search until comprehensive information is found
List Session References Tool
Lists available references to help the search tool identify accessible documents more efficiently and understand the scope of available materials
The Agentic Search Tool system provides several advantages over traditional reference handling:
Intelligent Navigation: Understands document structure and can move through sections systematically
Comprehensive Search: Continues searching until it has sufficient information to answer your question
Context Preservation: Maintains understanding of how different pieces of information relate to each other
Organizational Awareness: Respects and utilizes your document organization system
Tool Output Transparency: Each search shows as a collapsible knowledge search step in the conversation instead of the widget display
Scalable Access: Works with large reference collections without requiring manual subset selection
Agentic search needs a model that supports tool use. If your app uses a model that doesn’t, such as DeepSeek or Llama, it automatically falls back to the traditional reference system, so it still has access to your references.
With agentic search, the traditional “references used” widget no longer lists the snippets your app found. Instead, each search appears as a collapsible knowledge search step in the conversation, which you can expand to see what the app searched for and what it found. Pinned references are still included in every session as before.
Model Compatibility Requirements
Agentic search works with models that support tool use, which includes most models in Playlab. Apps on models without tool support, such as DeepSeek or Llama, automatically use the traditional reference system instead, so they never lose access to references.
Enhanced Search Behavior
Unlike the traditional system that stops after finding 10 similar snippets, the Agentic Search Tool will continue searching your documents until it has comprehensive information to answer your question. This means more thorough responses but potentially longer processing times for complex queries.
How does this differ from the traditional reference system?
The traditional system finds the 10 most similar snippets and stops there. The Agentic Search Tool works more like an intelligent research assistant that can navigate through your organized materials, understand document structures, and continue searching until it finds comprehensive information to answer your question. Instead of seeing a simple “references used” widget, you get detailed tool outputs showing the AI’s research process.
Will this work with my existing document organization?
Yes! The system is designed to respect and utilize whatever organizational structure you already have. Whether you organize by subject, grade level, unit, or any other system, the AI will learn your structure and navigate accordingly. You don’t need to reorganize your existing materials.
How many documents can this handle?
The system is designed to work with large collections of references. Rather than requiring you to manually select subsets for each app, you can give your app access to your entire reference collection. The AI will only search through documents that are relevant to the current conversation.
Do I need to turn anything on?
No. Both the References Search Tool and the List Session References Tool switch on automatically for any app with references. The List tool gives the Search tool a “table of contents” for your reference collection, which leads to faster and more accurate results.
What happens to my existing references?
Your uploaded reference documents remain unchanged and accessible. The tools simply provide a new, more powerful way to search and retrieve information from those same documents. All your content stays exactly where it is.
Which AI models work best with these tools?
For optimal performance with Agentic Search Tools:Tier 1 Performance (Recommended): Claude Sonnet 4.6 (excellent balance of search accuracy and response quality), GPT 5.4 (superior for complex document analysis and precise retrieval), Gemini 3.1 Pro (high accuracy with comprehensive document understanding), and Gemini 3.5 Flash (frontier-tier agentic performance at Flash-tier speed, ideal for multi-step retrieval workflows).Tier 2 Performance: Claude Opus 4.6 (most thorough document analysis but slower response times) and Kimi K2.5 (where allowed by law) (advanced tool usage with solid reference handling).Speed-Optimized Options: Claude Haiku 4.5 (faster searches with reduced analysis depth) and Gemini 3 Flash (quick queries for simple reference questions).Models without tool support automatically use the traditional reference system instead.
Can I still see which references are being used?
Yes, but in a more detailed format. Instead of the traditional “references used” widget, expand the knowledge search step in the conversation to see exactly which documents were searched, what queries were performed, what specific content was retrieved, and how the AI navigated through your materials. This provides much more transparency than the previous system.
What performance should I expect with different models?
Claude Sonnet 4.6 and GPT 5.4 typically provide search results in 2-6 seconds with high accuracy. Claude Opus 4.6 offers the most thorough document analysis but may take 5-12 seconds. Speed-optimized options like Claude Haiku 4.5 respond in 1-3 seconds but with simpler analysis suitable for basic reference queries.For comprehensive reference work requiring detailed document analysis, Claude Sonnet 4.6 or GPT 5.4 provide the optimal balance of speed, accuracy, and thorough search capabilities.
Can I turn agentic search off?
No. Agentic search is now the default for every app with references, and there’s no longer a toggle in the References panel. If you want specific content included in every session no matter what, pin that reference. Your documents and organization remain unchanged.
We’re continuously improving this tool based on user feedback. Contact our team at support@playlab.ai for implementation guidance, troubleshooting, or to share your success stories.Last updated: 09-28-2026
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Always check tool outputs for detailed reference information and cite sources appropriately.`})}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{})})]})})})]}),_jsxs(Step,{title:`Optimize Your Document Organization`,children:[_jsx(_components.p,{children:`For best results, organize your reference materials with:`}),_jsxs(_components.ul,{children:[`\n`,_jsxs(_components.li,{children:[_jsx(_components.strong,{children:`Descriptive file names`}),`: Use clear, specific names like “Grade-5-Math-Unit-3-Fractions-Teacher-Manual.pdf” instead of “Document1.pdf”`]}),`\n`,_jsxs(_components.li,{children:[_jsx(_components.strong,{children:`Well-structured documents`}),`: Files with clear headings and sections work best`]}),`\n`]})]}),_jsxs(Step,{title:`Test Different Query Types`,children:[_jsx(_components.p,{children:`Validate the tools work correctly by testing various query categories to search your reference files.`}),_jsxs(_components.p,{children:[_jsx(_components.strong,{children:`Multi-Step Research:`}),` “What are the prerequisites for teaching fractions, and what common misconceptions should I watch for?”`]})]})]}),`\n`,_jsx(Heading,{level:`2`,id:`understanding-the-agentic-search-system`,children:`Understanding the Agentic Search System`}),`\n`,_jsx(Heading,{level:`3`,id:`core-search-tools`,children:`Core Search Tools`}),`\n`,_jsxs(CardGroup,{cols:2,children:[_jsx(Card,{title:`References Search Tool`,icon:`search`,href:`#primary-search`,children:_jsx(_components.p,{children:`The primary search engine that queries your uploaded documents for specific information and content, continuing to search until comprehensive information is found`})}),_jsx(Card,{title:`List Session References Tool`,icon:`list`,href:`#reference-listing`,children:_jsx(_components.p,{children:`Lists available references to help the search tool identify accessible documents more efficiently and understand the scope of available materials`})})]}),`\n`,_jsx(Heading,{level:`3`,id:`key-features`,children:`Key Features`}),`\n`,_jsx(_components.p,{children:`The Agentic Search Tool system provides several advantages over traditional reference handling:`}),`\n`,_jsxs(_components.ul,{children:[`\n`,_jsxs(_components.li,{children:[_jsx(_components.strong,{children:`Intelligent Navigation`}),`: Understands document structure and can move through sections systematically`]}),`\n`,_jsxs(_components.li,{children:[_jsx(_components.strong,{children:`Comprehensive Search`}),`: Continues searching until it has sufficient information to answer your question`]}),`\n`,_jsxs(_components.li,{children:[_jsx(_components.strong,{children:`Context Preservation`}),`: Maintains understanding of how different pieces of information relate to each other`]}),`\n`,_jsxs(_components.li,{children:[_jsx(_components.strong,{children:`Organizational Awareness`}),`: Respects and utilizes your document organization system`]}),`\n`,_jsxs(_components.li,{children:[_jsx(_components.strong,{children:`Tool Output Transparency`}),`: Each search shows as a collapsible `,_jsx(_components.strong,{children:`knowledge search`}),` step in the conversation instead of the widget display`]}),`\n`,_jsxs(_components.li,{children:[_jsx(_components.strong,{children:`Scalable Access`}),`: Works with large reference collections without requiring manual subset selection`]}),`\n`]}),`\n`,_jsx(Note,{children:_jsx(_components.p,{children:`Agentic search needs a model that supports tool use. If your app uses a model that doesn’t, such as DeepSeek or Llama, it automatically falls back to the traditional reference system, so it still has access to your references.`})}),`\n`,_jsx(Heading,{level:`2`,id:`important-changes-in-behavior`,children:`Important Changes in Behavior`}),`\n`,_jsx(Accordion,{title:`Reference Widget Replacement`,id:`reference-widget-replacement`,children:_jsxs(_components.p,{children:[`With agentic search, the traditional “references used” widget no longer lists the snippets your app found. Instead, each search appears as a collapsible `,_jsx(_components.strong,{children:`knowledge search`}),` step in the conversation, which you can expand to see what the app searched for and what it found. `,_jsx(_components.a,{href:`/features/Pinned%20References`,children:`Pinned references`}),` are still included in every session as before.`]})}),`\n`,_jsx(Accordion,{title:`Model Compatibility Requirements`,id:`model-compatibility-requirements`,children:_jsx(_components.p,{children:`Agentic search works with models that support tool use, which includes most models in Playlab. Apps on models without tool support, such as DeepSeek or Llama, automatically use the traditional reference system instead, so they never lose access to references.`})}),`\n`,_jsx(Accordion,{title:`Enhanced Search Behavior`,id:`enhanced-search-behavior`,children:_jsx(_components.p,{children:`Unlike the traditional system that stops after finding 10 similar snippets, the Agentic Search Tool will continue searching your documents until it has comprehensive information to answer your question. This means more thorough responses but potentially longer processing times for complex queries.`})}),`\n`,_jsx(Heading,{level:`2`,id:`optimizing-your-reference-materials`,children:`Optimizing Your Reference Materials`}),`\n`,_jsx(Heading,{level:`3`,id:`supported-file-types`,children:`Supported File Types`}),`\n`,_jsx(_components.p,{children:`The system works with PDF, Word documents (.docx), and PowerPoint files (.pptx) through intelligent conversion that preserves document structure.`}),`\n`,_jsx(Heading,{level:`3`,id:`best-practices-for-organization`,children:`Best Practices for Organization`}),`\n`,_jsx(_components.p,{children:_jsx(_components.strong,{children:`File Naming Strategy:`})}),`\n`,_jsxs(_components.ul,{children:[`\n`,_jsxs(_components.li,{children:[`✅ Good: `,_jsx(_components.code,{children:`Grade-5-Math-Unit-3-Fractions-Teacher-Manual.pdf`})]}),`\n`,_jsxs(_components.li,{children:[`✅ Good: `,_jsx(_components.code,{children:`Science-Standards-Grade-6-Earth-Systems.docx`})]}),`\n`,_jsxs(_components.li,{children:[`❌ Avoid: `,_jsx(_components.code,{children:`Document1.pdf`}),` or `,_jsx(_components.code,{children:`H05JL - (copy 2).pdf`})]}),`\n`]}),`\n`,_jsx(_components.p,{children:_jsx(_components.strong,{children:`Folder Structure:`})}),`\n`,_jsxs(_components.ul,{children:[`\n`,_jsx(_components.li,{children:`Organize by subject area, grade level, unit, or topic`}),`\n`,_jsx(_components.li,{children:`Use consistent naming conventions`}),`\n`,_jsx(_components.li,{children:`Create logical hierarchies that match how you think about the content`}),`\n`,_jsx(_components.li,{children:`The AI will learn and respect your organizational choices`}),`\n`]}),`\n`,_jsx(_components.p,{children:_jsx(_components.strong,{children:`Document Quality:`})}),`\n`,_jsxs(_components.ul,{children:[`\n`,_jsx(_components.li,{children:`Well-structured documents with clear headings work best`}),`\n`,_jsx(_components.li,{children:`Consistent formatting helps the AI understand content relationships`}),`\n`,_jsx(_components.li,{children:`Documents with table of contents or clear section divisions are ideal`}),`\n`]}),`\n`,_jsx(Heading,{level:`2`,id:`frequently-asked-questions`,children:`Frequently Asked Questions`}),`\n`,_jsx(Accordion,{title:`How does this differ from the traditional reference system?`,id:`how-does-this-differ-from-the-traditional-reference-system`,children:_jsx(_components.p,{children:`The traditional system finds the 10 most similar snippets and stops there. The Agentic Search Tool works more like an intelligent research assistant that can navigate through your organized materials, understand document structures, and continue searching until it finds comprehensive information to answer your question. Instead of seeing a simple “references used” widget, you get detailed tool outputs showing the AI’s research process.`})}),`\n`,_jsx(Accordion,{title:`Will this work with my existing document organization?`,id:`will-this-work-with-my-existing-document-organization`,children:_jsx(_components.p,{children:`Yes! The system is designed to respect and utilize whatever organizational structure you already have. Whether you organize by subject, grade level, unit, or any other system, the AI will learn your structure and navigate accordingly. You don’t need to reorganize your existing materials.`})}),`\n`,_jsx(Accordion,{title:`How many documents can this handle?`,id:`how-many-documents-can-this-handle`,children:_jsx(_components.p,{children:`The system is designed to work with large collections of references. Rather than requiring you to manually select subsets for each app, you can give your app access to your entire reference collection. The AI will only search through documents that are relevant to the current conversation.`})}),`\n`,_jsx(Accordion,{title:`Do I need to turn anything on?`,id:`do-i-need-to-turn-anything-on`,children:_jsx(_components.p,{children:`No. Both the References Search Tool and the List Session References Tool switch on automatically for any app with references. The List tool gives the Search tool a “table of contents” for your reference collection, which leads to faster and more accurate results.`})}),`\n`,_jsx(Accordion,{title:`What happens to my existing references?`,id:`what-happens-to-my-existing-references`,children:_jsx(_components.p,{children:`Your uploaded reference documents remain unchanged and accessible. The tools simply provide a new, more powerful way to search and retrieve information from those same documents. All your content stays exactly where it is.`})}),`\n`,_jsxs(Accordion,{title:`Which AI models work best with these tools?`,id:`which-ai-models-work-best-with-these-tools`,children:[_jsx(_components.p,{children:`For optimal performance with Agentic Search Tools:`}),_jsxs(_components.p,{children:[_jsx(_components.strong,{children:`Tier 1 Performance (Recommended):`}),` Claude Sonnet 4.6 (excellent balance of search accuracy and response quality), GPT 5.4 (superior for complex document analysis and precise retrieval), Gemini 3.1 Pro (high accuracy with comprehensive document understanding), and Gemini 3.5 Flash (frontier-tier agentic performance at Flash-tier speed, ideal for multi-step retrieval workflows).`]}),_jsxs(_components.p,{children:[_jsx(_components.strong,{children:`Tier 2 Performance:`}),` Claude Opus 4.6 (most thorough document analysis but slower response times) and Kimi K2.5 (where allowed by law) (advanced tool usage with solid reference handling).`]}),_jsxs(_components.p,{children:[_jsx(_components.strong,{children:`Speed-Optimized Options:`}),` Claude Haiku 4.5 (faster searches with reduced analysis depth) and Gemini 3 Flash (quick queries for simple reference questions).`]}),_jsx(_components.p,{children:`Models without tool support automatically use the traditional reference system instead.`})]}),`\n`,_jsx(Accordion,{title:`Can I still see which references are being used?`,id:`can-i-still-see-which-references-are-being-used`,children:_jsxs(_components.p,{children:[`Yes, but in a more detailed format. 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Speed-optimized options like Claude Haiku 4.5 respond in 1-3 seconds but with simpler analysis suitable for basic reference queries.`}),_jsx(_components.p,{children:`For comprehensive reference work requiring detailed document analysis, Claude Sonnet 4.6 or GPT 5.4 provide the optimal balance of speed, accuracy, and thorough search capabilities.`})]}),`\n`,_jsx(Accordion,{title:`Can I turn agentic search off?`,id:`can-i-turn-agentic-search-off`,children:_jsxs(_components.p,{children:[`No. Agentic search is now the default for every app with references, and there’s no longer a toggle in the References panel. If you want specific content included in every session no matter what, `,_jsx(_components.a,{href:`/features/Pinned%20References`,children:`pin that reference`}),`. Your documents and organization remain unchanged.`]})}),`\n`,_jsx(Heading,{level:`2`,id:`need-support`,children:`Need Support?`}),`\n`,_jsxs(_components.p,{children:[`We’re continuously improving this tool based on user feedback. Contact our team at `,_jsx(_components.a,{href:`mailto:support@playlab.ai`,children:`support@playlab.ai`}),` for implementation guidance, troubleshooting, or to share your success stories.`]}),`\n`,_jsx(_components.hr,{}),`\n`,_jsx(_components.p,{children:_jsx(_components.em,{children:`Last updated: 09-28-2026`})})]})}function MDXContent(props={}){const{wrapper:MDXLayout}={..._provideComponents(),...props.components};return MDXLayout?_jsx(MDXLayout,{...props,children:_jsx(_createMdxContent,{...props})}):_createMdxContent(props)}return{default:MDXContent};function _missingMdxReference(id,component){throw new Error(`Expected `+(component?`component`:`object`)+\" `\"+id+\"` to be defined: you likely forgot to import, pass, or provide it.\")}","frontmatter":{},"scope":{"config":{},"pageMetadata":{"mode":"wide","title":"Improving referencing with agentic search tool","description":"Enhanced reference retrieval through AI-powered search tools that provide more precise and contextual access to your uploaded documents","sidebarTitle":"Improving Referencing with Agentic Search Tool","href":"/features/MCP RAG"}}},"mdxSourceWithNoJs":null},"mdxExtracts":{"tableOfContents":[{"title":"What is this feature?","slug":"what-is-this-feature","depth":2,"children":[]},{"title":"What is the Rationale for this feature?","slug":"what-is-the-rationale-for-this-feature","depth":2,"children":[]},{"title":"Watch How to Leverage the Agentic Search Tool","slug":"watch-how-to-leverage-the-agentic-search-tool","depth":2,"children":[]},{"title":"Setup Instructions","slug":"setup-instructions","depth":2,"children":[]},{"title":"Understanding the Agentic Search System","slug":"understanding-the-agentic-search-system","depth":2,"children":[{"title":"Core Search Tools","slug":"core-search-tools","depth":3,"children":[]},{"title":"Key Features","slug":"key-features","depth":3,"children":[]}]},{"title":"Important Changes in 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