name: deep-research
description: Use when user requests research requiring multiple sources, comprehensive analysis, or synthesis across topics - technical research, domain knowledge gathering, market analysis, or learning about complex subjects

Deep Research

Autonomous multi-agent research system. Dispatches parallel sub-agents, stores findings to files, synthesizes into briefs or reports.

Core principle: Planning → Parallel research agents → File-based findings → Synthesis = high quality research with minimal context usage.

When to Use

digraph when_to_use {
    "User requests research?" [shape=diamond];
    "Quick factual lookup?" [shape=diamond];
    "Use single search tool directly" [shape=box];
    "Multiple sources or synthesis needed?" [shape=diamond];
    "deep-research" [shape=box];

    "User requests research?" -> "Quick factual lookup?" [label="yes"];
    "Quick factual lookup?" -> "Use single search tool directly" [label="yes"];
    "Quick factual lookup?" -> "Multiple sources or synthesis needed?" [label="no"];
    "Multiple sources or synthesis needed?" -> "deep-research" [label="yes"];
}

Use for: Technical research, domain knowledge, market analysis, architectural patterns, comparing approaches, learning complex topics

Don't use for: Single fact lookups, specific URL fetches, questions answerable in one search

The Process

digraph process {
    rankdir=TB;

    "Create research directory in scratchpad" -> "Dispatch Query Analyzer agent";
    "Dispatch Query Analyzer agent" -> "Analyzer writes research-plan.md";
    "Analyzer writes research-plan.md" -> "Read plan, dispatch N Research agents IN PARALLEL";
    "Read plan, dispatch N Research agents IN PARALLEL" -> "Each agent writes findings-{thread}.md";
    "Each agent writes findings-{thread}.md" -> "Wait for all agents";
    "Wait for all agents" -> "Dispatch Synthesizer agent";
    "Dispatch Synthesizer agent" -> "Synthesizer reads all findings, writes final-output.md";
    "Synthesizer reads all findings, writes final-output.md" -> "Read final output, present summary to user";
}

Quick Reference

Phase 1: Planning (Query Analyzer Agent)

Uses ./query-analyzer-prompt.md. Writes research-plan.md containing:
- Query type: technical | domain | hybrid
- Complexity: simple (2-3 agents) | moderate (3-4) | complex (5-6)
- Research threads with source recommendations
- Output format recommendation: brief | report

Phase 2: Parallel Research

Uses ./research-agent-prompt.md. Each agent:
1. Invokes exa-search skill for source strategy
2. Executes searches (Exa-primary, see Source Selection below)
3. Writes findings-{thread-name}.md

Source Selection:

Phase 3: Synthesis

Uses ./synthesizer-prompt.md. Reads all findings files, writes final-output.md:
- Actionable Brief (~300 words): Simple query + clear consensus
- Structured Report (~1500 words): Complex query or conflicting findings

Agent Dispatch Methods

For complex queries (4+ threads): Use Task tool with subagent_type: "general-purpose" for true sub-agent isolation. Dispatch all research agents in a single message (parallel Task calls).

For simpler queries (2-3 threads): Parallel tool calls within same context is acceptable - make all searches simultaneously, then write findings files.

Either way: research threads must execute in parallel, not sequentially.

File Structure

{scratchpad}/deep-research-{timestamp}/
├── research-plan.md
├── findings-*.md
└── final-output.md

Common Mistakes

Red Flags - STOP

• "I'll just do a quick search myself" → Use the full process
• "I don't need to write files for this" → Files are mandatory
• "I'll research these topics one at a time" → Parallel dispatch
• "This is simple, I'll skip planning" → Always plan first