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    deep-research-team

    by 高紹育

    Deploy a hierarchical team of AI agents to perform 15-30 minute deep-dive research with parallel execution.

    26 developers installed this skill·Updated May 2026
    26 installs
    218 views

    Free

    One-time purchase

    ⚡ Also available via Agensi MCP — your AI agent can load this skill on demand via MCP. Learn more →

    Included in download

    • Downloadable skill package
    • 3 permissions declared
    • Instant install

    See it in action

    Quick Mode output structure:
ai_agent_ecosystem_2025/
├── 00_planning/research_plan.md
├── 01_platforms/research.md + sources.md (27 sources)
├── 02_technology/research.md + sources.md (30 sources)
├── 03_business/research.md + sources.md (25 sources)
└── final_report/executive_summary.md

Each research.md contains structured findings with data tables, key conclusions, and cross-references. Each sources.md logs every cited source with URL, type, confidence rating, and citation location. The executive summary synthesizes all modules into a single overview with key metrics, core findings, cross-module consensus/contradictions, and action recommendations.

    About This Skill

    Advanced Multi-Agent Research Orchestration

    The Deep Research Team skill transforms your AI environment into a high-powered research laboratory. Instead of relying on a single prompt that may hallucinate or miss nuances, this skill deploys a structured team of specialized agents that work in parallel to investigate, cross-validate, and synthesize complex information into publication-ready reports.

    What It Does

    The skill automates a multi-phase research workflow designed for depth and accuracy:

    • Phase 0 (Planning): A PM Agent designs a custom research architecture and directory structure based on your specific topic.
    • Phase A (Parallel Research): Multiple specialized agents are dispatched simultaneously to investigate different facets of the topic, ensuring high throughput and diverse perspectives.
    • Phase B & C (Synthesis & Audit): A Synthesis Agent identifies patterns and contradictions across findings, while a Review Agent (powered by high-reasoning models) performs a critical quality audit.
    • Phase D (Delivery): A Final Report Agent assembles a comprehensive document with a separate executive summary and full source citations.

    Why Use This Skill?

    Standard AI prompting often lacks the breadth needed for professional due diligence. This skill is superior because it uses a file-system relay for agent communication, preventing the "context drift" associated with long chat threads. It supports both a Quick Mode for rapid overviews and a Full Mode for academic-grade investigations, complete with automated quality scoring and error-checking.

    Output & Capabilities

    The result is a structured workspace containing individual module findings, a synthesis report, and a final executive summary. Every fact is mapped to its primary source, making it ideal for competitive analysis, investment research, and technical due diligence.

    Use Cases

    • Investment due diligence research
    • Competitive intelligence analysis
    • Technology evaluation and comparison
    • Market entry research

    Reviews

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    Security Scanned

    Passed automated security review

    Permissions

    Read Files
    Write Files
    Network Access

    File Scopes

    *.md

    Read Files: reads prompt templates and research outputs. Write Files: creates research reports and source files. Network Access: research agents use web search to gather sources.

    Tags

    deep-research
    multi-agent
    market-intelligence
    due-diligence
    report-generation
    technical-analysis

    Requires web search capability for research agents. Best with Claude Code. Compatible with any SKILL.md agent.

    Creator

    高紹育

    Frequently Asked Questions

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