deep-research
Execute autonomous multi-step deep research on any topic. Use when the user asks for comprehensive research, literature reviews, competitive analysis, topic deep-dives, or wants to understand a complex subject from multiple angles. Triggers on "deep research", "research on", "investigate", "literature review", "comprehensive analysis", "what do we know about", "summarize research on".
Best use case
deep-research is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Execute autonomous multi-step deep research on any topic. Use when the user asks for comprehensive research, literature reviews, competitive analysis, topic deep-dives, or wants to understand a complex subject from multiple angles. Triggers on "deep research", "research on", "investigate", "literature review", "comprehensive analysis", "what do we know about", "summarize research on".
Teams using deep-research should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/deep-research/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How deep-research Compares
| Feature / Agent | deep-research | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Execute autonomous multi-step deep research on any topic. Use when the user asks for comprehensive research, literature reviews, competitive analysis, topic deep-dives, or wants to understand a complex subject from multiple angles. Triggers on "deep research", "research on", "investigate", "literature review", "comprehensive analysis", "what do we know about", "summarize research on".
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Deep Research Autonomous multi-step research that searches multiple sources, reads full content, synthesizes findings, and produces a structured report. ## When to Use - User wants a thorough understanding of a topic (medical condition, drug, treatment, technology) - User asks for a literature review or evidence summary - User wants competitive or landscape analysis - User wants to investigate an open question with multiple angles - User asks "what does the research say about X" ## Research Strategy ### Step 1: Query Decomposition Break the research question into 3–5 sub-questions covering: - Core definition / mechanism - Current evidence / state of the art - Debates, limitations, or contradictions - Clinical / practical implications (if medical) - Recent developments (last 1–2 years) ### Step 2: Multi-Source Search Run searches across complementary sources using the available search tools: ```python # Use multi-search-engine for broad web coverage # Use pubmed-search for peer-reviewed medical literature # Use agent-browser to read full-text articles and retrieve content blocked by snippets ``` **Search order:** 1. PubMed (if medical/biomedical topic) — for peer-reviewed evidence 2. Multi-search-engine (Bing, Google, DuckDuckGo) — for guidelines, reviews, news 3. Wikipedia — for background and structured overviews 4. agent-browser — for reading full articles, PDFs, clinical guidelines ### Step 3: Source Evaluation For each source note: - Publication type (RCT, meta-analysis, guideline, review, news) - Date (prefer sources within 5 years for medical topics) - Authority (journal impact, organization credibility) - Relevance to the specific sub-question ### Step 4: Synthesis Synthesize across sources into a coherent narrative. Do NOT just concatenate summaries — identify: - Points of consensus - Contradictions or conflicting evidence - Knowledge gaps - Strongest evidence vs. weak/preliminary evidence ### Step 5: Structured Report Produce a well-formatted Markdown report with: ```markdown # [Topic] — Deep Research Report ## Summary 2–3 sentence executive summary of the key finding. ## Background What is this? Core definitions, mechanisms, or context. ## Current Evidence What does the research show? Organized by sub-question or theme. ## Key Debates / Open Questions Where do experts disagree? What is still unknown? ## Clinical / Practical Implications (For medical topics) What should clinicians or patients know? ## Recent Developments Anything notable from the past 12–24 months. ## Sources Numbered list of all sources with titles, URLs/DOIs, and dates. ``` ## Medical Research Guidelines When researching medical topics: - **Prioritize evidence hierarchy**: Systematic reviews > RCTs > Cohort studies > Case reports > Expert opinion - **Include safety information**: Drug interactions, contraindications, adverse effects - **Note population specifics**: Pediatric vs. adult, special populations, comorbidities - **Flag regulatory status**: FDA/EMA approval status, off-label use - **Cite clinical guidelines**: NICE, AHA, ACC, IDSA, WHO guidelines where relevant - **Distinguish mechanistic from clinical evidence**: Lab/animal data ≠ human evidence ## Depth Levels Adapt depth to user request: - **Quick overview** (user asks briefly): 3–5 sources, 1-page summary - **Standard research** (default): 8–15 sources, full structured report - **Comprehensive review** (user asks explicitly): 20+ sources, deep synthesis with evidence grading ## Example Execution **User:** "Research the evidence for metformin use in longevity/anti-aging" 1. Decompose: mechanism of action → RCT evidence → observational data → safety profile → current trials 2. Search PubMed for "metformin longevity aging", "TAME trial metformin" 3. Search web for "metformin anti-aging clinical trials 2024" 4. Read key papers with agent-browser 5. Synthesize: strong mechanistic evidence, TAME trial ongoing, limited long-term human RCT data 6. Produce structured report with citations
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