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Agent✓ Free🛡 Safety-reviewedClaude Code native⬇ 528 installs

Research Synthesizer

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>

Category: deep-research-teamBy: Daniel Ávila (davila7/claude-code-templates)License: MITSource repo ↗

Works with:Claude Code

Claude Code subagent/command format. Runs in Claude Code.

✓ Writes only inside the .claude/ folder you choose — nothing else is touched.

Or install via CLI:

npx configdeck add research-synthesizer

🛡 Safety-reviewedSafety review

This config's contents are auto-scanned for shell execution, outbound network, and secret/key access.

✓ No risky behavior detected.

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More in this category · deep-research-team

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.

Research Orchestrator

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>

Query Clarifier

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>

Competitive Intelligence Analyst

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

Research Coordinator

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>

Technical Researcher

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>