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deep-research

Execute autonomous multi-step deep research on any topic.

Skill by beita6969

IndexedMIT★ 1,019
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

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About

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".

Use cases: research

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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/deep-research

What's inside

Skill name
deep-research
Description
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".
License
MIT
Instructions
108 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# 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

From beita6969/ScienceClaw, MIT.

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Last commit (this folder)
Mar 12, 2026 (7 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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Cite this page

deep-research skill. Agent Mart. https://agentmart.dev/skills/beita6969-deep-research (last updated 2026-10-24)