deep-research-agent
Skill575 starsChanged 3 months agoMITView on GitHub
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".
2 other projects use a version of this.
Adopted by
Most recently taken up by
- garri333/Skillstheir own version, first seen Oct 11, 2026
- liangdabiao/deep-research-agent-skilltheir own version, first seen Aug 17, 2026
Other versions2 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 2
- liangdabiao/deep-research-agent-skill★ 3same name
- garri333/Skills★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository11 other files it gives its agents.
- AGENTS.mdAGENTS.md
- brainstormingSkill
- cavemanSkill
- frontend-designSkill
- improveSkill
- loop-meSkill
- memorySkill
- ponytailSkill
- deep-researchSkill
- ui-ux-pro-maxSkill
- web-scraperSkill
The file
We split this skill into the rules it gives an agent
7 rules. About 0 are common, 6 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈6
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 69
Ensure geographic diversity (US/EU/Asia when relevant)
- Distinctive: line 109
Check consistency across independent sources
- Distinctive: line 110
Verify statistics with multiple citations
- Distinctive: line 170
Every factual claim MUST have inline citation [source_id]
- Distinctive: line 173
Use tables for statistical comparisons
- Distinctive: line 180
Run independent searches in parallel (up to 10 concurrent queries)
- Distinctive: line 215
Source validation: All statistics must have minimum 3 source verification
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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 (natural language)
Process:
- 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)
- 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
- 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:
- 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)
- Source classification
- Categorize by source type: News, Academic Papers, Whitepapers, Technical Documentation, Forums, Blogs
- Assess domain authority and reliability
- Flag sources requiring deeper analysis
- 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)
- 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:
- Content extraction
- Access each promising URL
- Extract structured information: facts, statistics, quotes, dates, claims
- Parse PDF documents for detailed data
- Relevance assessment
- Score content against research objectives (1-5 scale)
- Filter out low-relevance or duplicate content
- Prioritize high-value sources for deep analysis
- 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) - 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:
- Cross-verification protocol
- Check consistency across independent sources
- Verify statistics with multiple citations
- Confirm quotes with original context
- Contradiction resolution
- Document conflicting information
- Assess source credibility differences
- Note the nature of disagreement (factual vs interpretive)
- Present multiple perspectives when resolution impossible
- Gap identification
- Compare gathered information against research plan
- Identify missing perspectives or outdated information
- Flag areas needing additional primary source verification
- 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
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

