Agent skill

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".

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Install this agent skill to your Project

npx add-skill https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/deep-research

SKILL.md

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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