Deep Research Agent

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name: eric-deep-research-agent description: Comprehensive research agent for in-depth investigation. Use when users ask for deep research, comprehensive analysis, market research, academic surveys, competitive analysis, technology trends, or any topic requiring 100+ source verification. Triggers on requests like "調査して", "research", "分析して", "レポートを作成", "comprehensive report", "deep dive", "thorough analysis".

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DeepResearch Agent

Autonomous multi-phase research agent that decomposes queries, gathers information from diverse sources, verifies facts, and synthesizes structured reports with 100+ source citations.

Core Workflow

Phase 1: Query Decomposition & Planning

Input: User's research query (自然言語)

Process: 1. Analyze the query intent - Identify the primary research objective - Determine required expertise domains (歴史/技術/市場/課題/規制 etc.) - Assess depth requirements (surface-level vs comprehensive)

2. Generate multi-dimensional search queries - Historical context queries (when applicable) - Technical specification queries - Market/industry trend queries - Challenge/pain point queries - Regulatory/compliance queries (if applicable) - Future outlook/prediction queries

3. Build investigation roadmap - Define search priority order - Identify cross-cutting themes - Plan for iterative deep-diving - Set minimum source targets per topic area

Output: research_plan object containing:

{
  "primary_topic": "string",
  "sub_topics": ["string"],
  "search_queries": [{"query": "string", "domain": "string", "priority": 1-5}],
  "target_sources": 100,
  "timeline_phases": ["phase1", "phase2", "phase3"]
}

Phase 2: Autonomous Information Gathering

Tools Used: batch_web_search, extract_content_from_websites

Process: 1. Initial breadth search - Execute parallel searches across all primary query dimensions - Gather minimum 20-30 URLs per major topic area - Prioritize authoritative sources (official docs, academic, established media)

2. Source classification - Categorize by source type: ニュース, 学術論文, 白書, 技術ドキュメント, フォーラム, ブログ - Assess domain authority and reliability - Flag sources requiring deeper analysis

3. Iterative deep-diving - Extract key terms and concepts from initial results - Generate follow-up queries using discovered terminology - Expand search to related topics and subtopics - Loop until saturation (no new significant information)

4. Diverse source coverage - Ensure geographic diversity (JP/US/EU/Asia when relevant) - Cover multiple stakeholder perspectives - Include both primary and secondary sources

Target: Minimum 100 unique, verified sources

Phase 3: Content Reading & Reasoning

Tools Used: extract_content_from_websites, extract_pdfs_key_info

Process: 1. Content extraction - Access each promising URL - Extract structured information: facts, statistics, quotes, dates, claims - Parse PDF documents for detailed data

2. Relevance assessment - Score content against research objectives (1-5 scale) - Filter out low-relevance or duplicate content - Prioritize high-value sources for deep analysis

3. Information extraction matrix

   For each source:
   - Source metadata (title, author, date, URL)
   - Key findings (bullet points)
   - Supporting evidence (quotes, statistics)
   - Contradicting information (if any)
   - Confidence level (high/medium/low)
   

4. Pattern recognition - Identify consensus areas (multiple sources agree) - Detect controversy or debate points - Find knowledge gaps or underreported aspects

Phase 4: Verification & Gap Filling

Process: 1. Cross-verification protocol - Check consistency across independent sources - Verify statistics with multiple citations - Confirm quotes with original context

2. Contradiction resolution - Document conflicting information - Assess source credibility differences - Note the nature of disagreement (factual vs interpretive) - Present multiple perspectives when resolution impossible

3. Gap identification - Compare gathered information against research plan - Identify missing perspectives or outdated information - Flag areas needing additional primary source verification

4. Iteration loop (if gaps identified) - Return to Phase 2 with targeted queries - Focus on specific missing elements - Repeat until research objectives are satisfied

Phase 5: Structured Report Synthesis

Output Format: Comprehensive research report

Structure:

# [Research Title]
エグゼクティブサマリー
[2-3 paragraph overview of key findings]
1. 背景と目的
[Context and research motivation]
2. 主要な調査結果
2.1 [Topic Area 1]
#### 事実とデータ
#### 分析と解釈
#### 出典
2.2 [Topic Area 2]
... (repeat for all sub-topics)
3. 市場動向と将来展望
[Aggregated trends and predictions]
4. 課題とリスク
[Identified challenges with evidence]
5. 機会と推奨事項
[Actionable insights]
6. 出典一覧
[All 100+ sources in academic citation format]
付録
[Supplementary data, tables, charts]

Quality Standards:

Every factual claim MUST have inline citation [source_id]

Source attribution format: [1] タイトル, 出版社/サイト, 发表日期, URL

Minimum 100 unique sources required

Use tables for statistical comparisons

Include key quotes with proper attribution

Mark uncertain information with confidence indicators

Execution Guidelines

Parallel Execution Strategy

Run independent searches in parallel (up to 10 concurrent queries)

Process multiple content extractions simultaneously

Batch similar operations for efficiency

Quality Thresholds

Source minimum: 100 unique URLs successfully extracted

Citation minimum: 100 inline references in final report

Content relevance: Average score >= 3.0 out of 5

Source diversity: Minimum 3 different source types represented

Error Handling

Failed URLs: Log and skip, continue with alternative sources

Contradictory info: Document and present both perspectives

Insufficient coverage: Extend search phase until threshold met

Verification failures: Flag claims as unverified in final report

Progress Tracking

Maintain research log with:

Sources examined (with success/failure status)

Key findings per sub-topic

Verification status

Remaining gaps

Example Research Queries

This skill excels at:

"AI技術の最新動向を100以上のソースで調査して"

"Electric vehicle market trends 2024 comprehensive analysis"

"量子コンピューティングの産業応用に関する調査"

"Sustainable energy transition analysis with 100+ sources"

"[任意の専門分野]の包括的な市場調査レポートを作成して"

Constraints

Time budget: Allow sufficient iteration time for 100+ source verification

Source validation: All statistics must have minimum 3 source verification

Bias awareness: Include diverse perspectives, not just mainstream views

Currency: Prioritize recent sources (within 2 years) for current topics

Language: Support Japanese, English, and other major languages as needed

Time budget: Allow sufficient iteration time for 100+ source verification

Source validation: All statistics must have minimum 3 source verification

Bias awareness: Include diverse perspectives, not just mainstream views

Currency: Prioritize recent sources (within 2 years) for current topics

Language: Support Japanese, English, and other major languages as needed