Deep Research Team · 12 configs

Expert research agent specialized in leveraging Nia's knowledge tools. Use PROACTIVELY for discovering repos/docs, deep technical research, remote codebases exploration, documentation queries, and cross-agent knowledge handoffs. Automatically indexes and searches discovered resources.

Use this agent when you need to coordinate a comprehensive research project that requires multiple specialized agents working in sequence. This agent manages the entire research workflow from initial query clarification through final report generation. <example>Context: User wants to conduct thorough research on a complex topic. user: "I need to research the impact of quantum computing on cryptography" assistant: "I'll use the research-orchestrator agent to coordinate a comprehensive research project on this topic" <commentary>Since this is a complex research request requiring multiple phases and specialized agents, the research-orchestrator will manage the entire workflow.</commentary></example> <example>Context: User has a vague research request that needs clarification and systematic investigation. user: "Tell me about AI safety" assistant: "Let me use the research-orchestrator to coordinate a structured research process on AI safety" <commentary>The broad nature of this query requires orchestration of multiple research phases, making the research-orchestrator the appropriate choice.</commentary></example>

Use this agent when you need to analyze research queries for clarity and determine if user clarification is needed before proceeding with research. This agent should be invoked at the beginning of research workflows to ensure queries are specific and actionable. Examples: <example>Context: The user has created a query-clarifier agent to analyze research queries for clarity. user: "Tell me about AI" assistant: "I'll use the query-clarifier agent to analyze this query for clarity and determine if we need more specific information." <commentary>Since the query is quite broad and could refer to many aspects of AI, the query-clarifier agent should analyze it and likely request clarification about which specific aspect of AI the user is interested in.</commentary></example> <example>Context: The user has created a query-clarifier agent to ensure research queries are actionable. user: "Compare the performance of different sorting algorithms in terms of time complexity" assistant: "Let me analyze this query with the query-clarifier agent to ensure it's clear and specific enough for research." <commentary>This query is relatively clear but the agent should still analyze it to confirm no clarification is needed before proceeding with the research.</commentary></example>

Specialist in reverse-engineering competitor strategy from observable signals—pricing moves, hiring patterns, product launches, partnership announcements, patent filings, and executive communications. Produces actionable

Use this agent when you need to strategically plan and coordinate complex research tasks across multiple specialist researchers. This agent analyzes research requirements, allocates tasks to appropriate specialists, and defines iteration strategies for comprehensive coverage. <example>Context: The user has asked for a comprehensive analysis of quantum computing applications in healthcare. user: "I need a thorough research report on how quantum computing is being applied in healthcare, including current implementations, future potential, and technical challenges" assistant: "I'll use the research-coordinator agent to plan this complex research task across our specialist researchers" <commentary>Since this requires coordinating multiple aspects (technical, medical, current applications), use the research-coordinator to strategically allocate tasks to different specialist researchers.</commentary></example> <example>Context: The user wants to understand the economic impact of AI on job markets. user: "Research the economic impact of AI on job markets, including statistical data, expert opinions, and case studies" assistant: "Let me engage the research-coordinator agent to organize this multi-faceted research project" <commentary>This requires coordination between data analysis, academic research, and current news, making the research-coordinator ideal for planning the research strategy.</commentary></example>

Use this agent when you need to analyze code repositories, technical documentation, implementation details, or evaluate technical solutions. This includes researching GitHub projects, reviewing API documentation, finding code examples, assessing code quality, tracking version histories, or comparing technical implementations. <example>Context: The user wants to understand different implementations of a rate limiting algorithm. user: "I need to implement rate limiting in my API. What are the best approaches?" assistant: "I'll use the technical-researcher agent to analyze different rate limiting implementations and libraries." <commentary>Since the user is asking about technical implementations, use the technical-researcher agent to analyze code repositories and documentation.</commentary></example> <example>Context: The user needs to evaluate a specific open source project. user: "Can you analyze the architecture and code quality of the FastAPI framework?" assistant: "Let me use the technical-researcher agent to examine the FastAPI repository and its technical details." <commentary>The user wants a technical analysis of a code repository, which is exactly what the technical-researcher agent specializes in.</commentary></example>

Use this agent when you need to transform a user's research query into a structured, actionable research brief that will guide subsequent research activities. This agent takes clarified queries and converts them into comprehensive research plans with specific questions, keywords, source preferences, and success criteria. <example>Context: The user has asked a research question that needs to be structured into a formal research brief.\nuser: "I want to understand the impact of AI on healthcare diagnostics"\nassistant: "I'll use the research-brief-generator agent to transform this query into a structured research brief that will guide our research."\n<commentary>Since we need to create a structured research plan from the user's query, use the research-brief-generator agent to break down the question into specific sub-questions, identify keywords, and define research parameters.</commentary></example><example>Context: After query clarification, we need to create a research framework.\nuser: "How are quantum computers being used in drug discovery?"\nassistant: "Let me use the research-brief-generator agent to create a comprehensive research brief for investigating quantum computing applications in drug discovery."\n<commentary>The query needs to be transformed into a structured brief with specific research questions and parameters, so use the research-brief-generator agent.</commentary></example>

Use this agent when you need to consolidate and synthesize findings from multiple research sources or specialist researchers into a unified, comprehensive analysis. This agent excels at merging diverse perspectives, identifying patterns across sources, highlighting contradictions, and creating structured insights that preserve the complexity and nuance of the original research while making it more accessible and actionable. <example>Context: The research-orchestrator has completed Phase 4 parallel research on 'LLM fine-tuning costs' using academic-researcher, web-researcher, and data-analyst. user: "Synthesize the research outputs." assistant: "I'll invoke the research-synthesizer agent to merge all specialist findings into a unified analysis." <commentary>The orchestrator has confirmed all three researcher outputs exist as files, making this the correct trigger point for synthesis. The agent will locate each output file, extract claims, and produce both synthesis-summary.md and synthesis.json.</commentary></example> <example>Context: The research-orchestrator has completed parallel research on 'WASM adoption in server-side runtimes' using academic-researcher, web-researcher, and technical-researcher. All three output files are confirmed present. user: "All researchers are done. Synthesize everything into a report." assistant: "Let me use the research-synthesizer agent to consolidate the three specialist outputs into a structured synthesis." <commentary>Three distinct researcher outputs referencing the same topic are present; the synthesis agent is the correct next step to unify them and surface contradictions and shared themes.</commentary></example>

Fact verification and source validation specialist. Use PROACTIVELY for claim verification, source credibility assessment, misinformation detection, citation validation, and information accuracy analysis.

Use this agent when you need to transform synthesized research findings into a comprehensive, well-structured final report. This agent excels at creating readable narratives from complex research data, organizing content logically, and ensuring proper citation formatting. It should be used after research has been completed and findings have been synthesized, as the final step in the research process. Examples: <example>Context: The user has completed research on climate change impacts and needs a final report. user: 'I've gathered all this research on climate change effects on coastal cities. Can you create a comprehensive report?' assistant: 'I'll use the report-generator agent to create a well-structured report from your research findings.' <commentary>Since the user has completed research and needs it transformed into a final report, use the report-generator agent to create a comprehensive, properly formatted document.</commentary></example> <example>Context: Multiple research threads have been synthesized and need to be presented cohesively. user: 'We have findings from 5 different researchers on AI safety. Need a unified report.' assistant: 'Let me use the report-generator agent to create a cohesive report that integrates all the research findings.' <commentary>The user needs multiple research streams combined into a single comprehensive report, which is exactly what the report-generator agent is designed for.</commentary></example>

[Open Deep Research Team Diagram](../../../images/research_team_diagram.html)

Academic research specialist for scholarly sources, peer-reviewed papers, and academic literature. Use PROACTIVELY for research paper analysis, literature reviews, citation tracking, and academic methodology evaluation.