Deep Research Pro

Deep Research Pro is a community skill for multi-source research automation, covering web search integration, finding synthesis, citation tracking, report generation, and comprehensive analysis for in-depth research projects requiring multiple information sources.

What Is This?

Overview

Deep Research Pro provides AI agents with advanced research capabilities that search multiple sources, synthesize findings, and deliver cited reports for comprehensive analysis. It covers web search integration that queries multiple search engines and academic databases to gather diverse information sources automatically, finding synthesis that analyzes collected information to identify patterns, contradictions, and key insights across sources, citation tracking that maintains source attribution and generates proper references for all claims and data points in reports, report generation that structures research findings into comprehensive documents with executive summaries, detailed analysis, and bibliography sections, and source evaluation that assesses credibility and relevance of information based on publication dates, author credentials, and cross-reference validation. The skill enables thorough research projects that would require hours of manual investigation and synthesis work.

Who Should Use This

This skill serves researchers conducting literature reviews, business analysts investigating market trends, and AI agents requiring comprehensive information synthesis from multiple sources.

Why Use It?

Problems It Solves

Manual research across multiple sources is time consuming and requires reading dozens of documents for comprehensive understanding. Synthesizing findings from diverse sources demands careful comparison and integration of potentially contradictory information. Tracking citations and maintaining proper source attribution throughout research projects is tedious and error prone. Structuring research findings into coherent reports requires significant writing effort and organizational planning. Evaluating source credibility and detecting bias requires domain expertise and critical analysis skills.

Core Highlights

Search aggregator queries multiple sources including web, academic databases, and news for comprehensive coverage. Finding synthesizer analyzes collected information to identify patterns and insights across sources. Citation manager tracks source attribution and generates proper references automatically. Report builder structures findings into comprehensive documents with summaries and analysis.

How to Use It?

Basic Usage

from deep_research import \
    ResearchAgent

agent = ResearchAgent()

report = agent.research(
    topic=(
        'Impact of AI on '
        'software development'
    ),
    depth='comprehensive',
    sources=['web', 'academic',
             'news']
)

print(report.summary)
print(report.findings)
print(report.citations)

Real-World Examples

market_report = agent.research(
    topic='EV battery technology',
    focus=[
        'current state',
        'key players',
        'trends',
        'challenges'
    ],
    time_range='last_2_years',
    min_sources=20
)

market_report.export(
    'research_report.pdf',
    include_bibliography=True
)

comp_analysis = agent.research(
    topic='CRM software comparison',
    sources=['reviews', 'docs',
             'case_studies'],
    competitors=[
        'Salesforce',
        'HubSpot',
        'Pipedrive'
    ]
)

Advanced Tips

Specify time ranges to focus research on recent developments and avoid outdated information in fast-moving fields. Use focus keywords to guide synthesis toward specific aspects of broad topics for more targeted analysis. Set minimum source thresholds to ensure comprehensive coverage before accepting research conclusions as sufficiently validated.

When to Use It?

Use Cases

Conduct comprehensive literature reviews for academic research projects by aggregating findings from journals, conference papers, and preprints. Generate competitive intelligence reports by researching multiple companies, their products, market positioning, and customer feedback across diverse sources. Investigate emerging technologies and trends by synthesizing information from technical blogs, research papers, industry news, and expert commentary.

Related Topics

Research automation, information synthesis, literature review, competitive intelligence, citation management, report generation, and knowledge discovery.

Important Notes

Requirements

Access to multiple information sources including web search APIs, academic databases, and news aggregators for comprehensive coverage. Sufficient processing time for thorough research since deep analysis requires sequential source evaluation and synthesis. Understanding of research topic domain to evaluate generated findings and validate synthesis accuracy critically.

Usage Recommendations

Do: specify clear research questions and focus areas to guide synthesis toward actionable insights. Review generated citations to verify source accuracy and relevance before using reports professionally. Set appropriate depth parameters balancing comprehensiveness with time constraints for your research needs.

Don't: rely solely on automated research for critical decisions without expert review and validation. Skip source evaluation since AI synthesis may include unreliable or biased information sources. Assume complete coverage since some specialized databases and paywalled sources may not be accessible through search.

Limitations

Research quality depends on source availability and may miss specialized databases requiring institutional access. Synthesis accuracy varies with topic complexity and may require expert review for specialized domains. Processing time increases significantly with research depth and source count, potentially taking minutes to hours for comprehensive projects. Citation accuracy depends on source parsing and may require manual verification for formal publication use.