How to Build a Research Agent with OpenClaw

Building an OpenClaw research agent gives you an always-available research assistant that can investigate topics, synthesize information from multiple sources, track ongoing topics over time, and deliver formatted research reports. This guide covers building a research agent for personal or professional use.

What Makes a Good Research Agent?

A research agent needs:

• Multi-source search: Query multiple sources and cross-reference
• Source credibility assessment: Distinguish reliable from unreliable sources
• Synthesis capability: Combine information into coherent summaries
• Citation tracking: Keep track of where information came from
• Long-term topic monitoring: Follow topics over time, not just one-off queries

Required Skills

python -m openclaw skill install web-search     # General web search
python -m openclaw skill install brave-search   # Alternative search engine
python -m openclaw skill install arxiv-search   # Academic papers
python -m openclaw skill install web-browse     # Deep page reading
python -m openclaw skill install memory         # Persistent knowledge base

Research Agent System Prompt

Craft a system prompt that focuses your agent on research quality:

You are a research assistant. Your primary function is to find, evaluate, 
and synthesize information accurately.

Research principles:
- Always cite sources with URLs
- Prefer primary sources over secondary
- Note when information is uncertain or contested
- Flag any contradictions between sources
- Distinguish between facts, analysis, and opinion
- Include publication date for time-sensitive information
- Never speculate or extrapolate beyond what sources state

Workflow 1: One-Shot Research

"Research the current state of quantum computing commercialization. I need: major players, key milestones from the past 12 months, current capabilities vs. claims, and realistic timeline to practical applications. Cite all sources."

Your agent conducts multiple searches, reads key pages, and synthesizes a 500–1000 word research brief with citations.

Workflow 2: Ongoing Topic Monitoring

Configure your agent to monitor a topic weekly:

{
  "scheduler": {
    "tasks": [{
      "name": "weekly_research_digest",
      "cron": "0 9 * * 1",
      "action": "run",
      "prompt": "Search for news and developments in [your research topic] from the past 7 days. Compare to what you already know about this topic. Summarize new developments and their significance.",
      "output_channel": "telegram"
    }]
  }
}

Workflow 3: Literature Review

"I'm researching [academic topic]. Search arXiv for papers published in the past 2 years. Identify the 5 most-cited recent papers, summarize their key findings, and identify any emerging consensus or controversies."

Workflow 4: Competitive Research

"Research [Competitor Company]. Find: their latest product updates, pricing changes, key hires, funding news, customer reviews (positive and negative), and what their customers say about their pain points."

Building a Research Knowledge Base

After each research session, instruct your agent:

"Save the key findings from this research to memory under the topic 'quantum computing'. Tag as research-note with today's date."

Over time, your agent builds a personal knowledge base that it references in future conversations.

Frequently Asked Questions

How does OpenClaw handle conflicting information from different sources?

Configure your agent to flag conflicts explicitly: "If you find contradictory information in different sources, note the contradiction and indicate which source appears more authoritative and why."

Can the research agent read PDFs?

Yes. The web-browse skill can extract text from PDF URLs. For locally stored PDFs, the read-file skill handles local file access.

How do I get academic paper access behind paywalls?

The arXiv skill accesses open-access papers. For paywalled journals, some institutions provide API access. Alternatively, many papers have preprint versions on arXiv or the author's academic page.