DeepResearch Agent

SkillAI & models

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 "investigate", "research", "analyze", "create a report", "comprehensive report", "deep dive", "thorough analysis".

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the DeepResearch Agent skill

What this skill tells your AI

The instructions your AI receives, as published by shobcoder/shob in skills/deep-research-agent/SKILL.md and read by ahel’s review.

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 (natural language)

Process:

  1. Analyze the query intent

    • Identify the primary research objective
    • Determine required expertise domains (History/Technology/Market/Challenges/Regulations 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}],
  "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: News, Academic Papers, Whitepapers, Technical Documentation, Forums, Blogs
    • 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 (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]

## Executive Summary
[2-3 paragraph overview of key findings]

## 1. Background and Purpose
[Context and research motivation]

## 2. Key Findings

### 2.1 [Topic Area 1]
#### Facts and Data
#### Analysis and Interpretation
#### Sources

### 2.2 [Topic Area 2]
... (repeat for all sub-topics)

## 3. Market Trends and Future Outlook
[Aggregated trends and predictions]

## 4. Challenges and Risks
[Identified challenges with evidence]

## 5. Opportunities and Recommendations
[Actionable insights]

## 6. List of Sources
[All 100+ sources in academic citation format]

## Appendix
[Supplementary data, tables, charts]

Quality Standards:

  • Every factual claim MUST have inline citation [source_id]
  • Source attribution format: [1] Title, Publisher/Site, Publication Date, 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:

  • "Investigate the latest trends in AI technology using 100+ sources"
  • "Electric vehicle market trends 2024 comprehensive analysis"
  • "Research on industrial applications of quantum computing"
  • "Sustainable energy transition analysis with 100+ sources"
  • "Create a comprehensive market research report on [any specialized field]"

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 English and other major languages as needed

Signals

GitHub stars
581
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
deep-research-agent
Source
github.com/shobcoder/shob