DevHive-Cli deep-research
Conduct thorough, multi-source research on complex topics with structured findings and citations.
git clone https://github.com/El3tar-cmd/DevHive-Cli
T=$(mktemp -d) && git clone --depth=1 https://github.com/El3tar-cmd/DevHive-Cli "$T" && mkdir -p ~/.claude/skills && cp -r "$T/agents/deep-research" ~/.claude/skills/el3tar-cmd-devhive-cli-deep-research && rm -rf "$T"
agents/deep-research/SKILL.mdDeep Research
Conduct comprehensive, multi-source research on complex topics. Systematically gather, evaluate, and synthesize information into structured reports with proper citations.
When to Use
- User needs thorough research on a complex topic
- User asks "research this," "find out about," or "do a deep dive on"
- User needs a literature review, market analysis, or technology evaluation
- User wants to understand a topic from multiple angles with cited sources
- User needs to verify claims or compare conflicting information
When NOT to Use
- Simple factual lookups (just use web-search directly)
- Searching within the user's own codebase (use grep/glob)
- Looking up Replit-specific features (use replit-docs skill)
- Product recommendations without research depth (use a more specific skill)
Research Architecture
This skill follows a tree-like exploration pattern inspired by leading open-source research tools:
- GPT Researcher (github.com/assafelovic/gpt-researcher, ~17k stars) -- uses "plan and execute" with parallel sub-question research
- STORM (github.com/stanford-oval/storm, ~18k stars) -- Stanford's perspective-guided research that simulates multiple expert viewpoints
- open_deep_research (github.com/langchain-ai/open_deep_research) -- LangChain's iterative search-and-synthesize approach
The core pattern: decompose the question -> search broadly -> read deeply -> identify gaps -> refine queries -> synthesize with citations.
Methodology
Phase 1: Scope Definition
Before starting research, clearly define:
- Research question: What specific question(s) are you answering?
- Scope boundaries: What is in/out of scope?
- Depth level: Overview, moderate analysis, or exhaustive deep-dive?
- Output expectations: Report format, length, audience
Phase 2: Parallel Source Discovery via Subagents
Decompose the topic into 5 distinct focus areas, then launch 5 research subagents in parallel using
startAsyncSubagent. Each subagent gets a specific focus area and set of search terms, searches independently, and returns its findings with citations.
How to decompose: After the broad landscape search in Phase 1, identify 5 non-overlapping angles. For example, researching "state of electric vehicles 2026" might decompose into:
- Market & Competition — market share, sales figures, manufacturer rankings
- Technology — battery chemistry, charging standards, range improvements
- Policy & Regulation — government incentives, emissions mandates, trade tariffs
- Infrastructure — charging network growth, grid capacity, urban vs rural
- Consumer & Economics — total cost of ownership, resale value, adoption demographics
Launch all 5 in parallel:
// Launch 5 research subagents simultaneously await startAsyncSubagent({ task: `Research FOCUS AREA 1: [Market & Competition] Topic context: [brief description of the overall research question] Your job: Search for information specifically about [focus area]. Run at least 3-4 webSearch queries with different angles: - [specific search term 1] - [specific search term 2] - [specific search term 3] - [specific search term 4] For the most promising results, use webFetch to read the full article. Return your findings as a structured summary with: - Key facts and data points (with source URLs) - Notable claims that need cross-referencing - Gaps or unanswered questions - At least 5 distinct sources with URLs` }); // Repeat for focus areas 2-5 with their own tailored search terms await startAsyncSubagent({ task: `Research FOCUS AREA 2: [Technology] ...` }); await startAsyncSubagent({ task: `Research FOCUS AREA 3: [Policy & Regulation] ...` }); await startAsyncSubagent({ task: `Research FOCUS AREA 4: [Infrastructure] ...` }); await startAsyncSubagent({ task: `Research FOCUS AREA 5: [Consumer & Economics] ...` }); // Wait for all subagents to complete const results = await waitForBackgroundTasks();
Each subagent should:
- Run 3-4
queries with different phrasings and angleswebSearch - Use
on the 2-3 most relevant results to extract detailed datawebFetch - Return structured findings with source URLs
- Flag any claims that conflict with other results
This approach gathers 25+ distinct sources across 5 focus areas simultaneously, producing far more comprehensive coverage than sequential searching.
After collecting all subagent results, proceed to Phase 3 to evaluate and cross-reference.
Phase 3: Source Evaluation
Assess each source for credibility:
- Authority: Who published it? What are their credentials?
- Currency: When was it published? Is the information still current?
- Objectivity: Is there obvious bias? Is it sponsored content?
- Accuracy: Can claims be cross-referenced with other sources?
- Coverage: Does it cover the topic in sufficient depth?
Use webFetch to read full articles from the most promising search results.
Phase 4: Information Synthesis
Organize findings thematically (what separates deep research from simple search):
- Group related findings across sources
- Identify areas of consensus and disagreement
- Note gaps in available information -- conduct follow-up searches to fill them
- Cross-reference critical claims across at least 2-3 independent sources
- Build a narrative that answers the research question
- Distinguish between established facts, expert opinions, and speculation
- Draw connections between sources that reveal patterns not visible in any single source
Phase 5: Report Writing
Structure the final report clearly:
- Lead with the most important findings
- Support claims with specific sources
- Acknowledge limitations and uncertainties
- Provide actionable recommendations where appropriate
Output Format
Research Report Structure
# [Research Topic] ## Executive Summary [2-3 paragraph overview of key findings and conclusions] ## Background [Context needed to understand the topic] ## Key Findings ### Finding 1: [Theme] [Detailed analysis with source citations] ### Finding 2: [Theme] [Detailed analysis with source citations] ### Finding 3: [Theme] [Detailed analysis with source citations] ## Analysis [Cross-cutting analysis, patterns, implications] ## Limitations [What couldn't be determined, data gaps, caveats] ## Recommendations [Actionable next steps based on findings] ## Sources [Numbered list of all sources with URLs]
Best Practices
- Cast a wide net first, then narrow -- start with broad searches before diving into specifics
- Cross-reference critical claims -- never rely on a single source for important facts
- Cite everything -- every factual claim should trace back to a source
- Note disagreements -- when sources conflict, present both sides and analyze why
- Timestamp your research -- note when the research was conducted, as information changes
- Separate facts from analysis -- clearly distinguish between what sources say and your interpretation
Example Workflow
// Phase 1: Broad landscape search to identify focus areas const overview = await webSearch({ query: "state of electric vehicle market 2026" }); // Phase 2: Launch 5 parallel research subagents await startAsyncSubagent({ task: `Research EV Market & Competition: search for "EV market share by manufacturer 2025 2026", "electric vehicle sales global rankings", "Tesla BYD market share comparison". Use webFetch on best results. Return findings with source URLs.` }); await startAsyncSubagent({ task: `Research EV Battery Technology: search for "solid state battery progress 2026", "EV battery cost per kwh trend", "lithium iron phosphate vs NMC comparison". Use webFetch on best results. Return findings with source URLs.` }); await startAsyncSubagent({ task: `Research EV Policy & Regulation: search for "EV tax credit policy 2026", "emissions regulations electric vehicles", "EV tariffs trade policy". Use webFetch on best results. Return findings with source URLs.` }); await startAsyncSubagent({ task: `Research EV Charging Infrastructure: search for "EV charging network growth statistics", "NACS vs CCS charging standard adoption", "fast charging stations by country". Use webFetch on best results. Return findings with source URLs.` }); await startAsyncSubagent({ task: `Research EV Consumer Economics: search for "EV total cost of ownership vs gas 2026", "electric vehicle resale value trends", "EV adoption demographics income". Use webFetch on best results. Return findings with source URLs.` }); // Collect all results const results = await waitForBackgroundTasks(); // Phase 3-5: Evaluate sources, cross-reference claims, synthesize into structured report // Write comprehensive report with all findings and citations from all 5 subagents
Limitations
- Cannot access paywalled academic journals or subscription databases
- Cannot access social media content (LinkedIn, Twitter, Reddit)
- Web sources may have varying levels of reliability
- Research is a snapshot in time -- findings may change
- Cannot conduct primary research (surveys, interviews, experiments)