OpenClaw Research Report System

Background

Research workflows often suffer from:

• Sources scattered and hard to compare
• Unstructured notes and inconsistent format
• Slow first-draft production
• Missing or weak citations

This use case builds collect → extract → structure → report.

Key steps

1. Define research question and scope.
2. Collect sources: web search, articles, reports, internal docs.
3. Extract key facts: per source, with attribution.
4. Structure analysis: sections, comparison tables, conclusions.
5. Generate report: intro, body, recommendations, sources.

Workflow sketch

Query → Fetch sources (Tavily) → Extract facts per source → Structure → Draft report with citations

Skill recommendations

openclaw skills install @clawhub/tavily
openclaw skills install @clawhub/summarize

Expected results

• Source list with URLs and summaries
• Extracted facts with clear attribution
• Structured report following a template
• Citations for all major claims

Common pitfalls

• Claiming conclusions without source backing
• Mixing source quality without flagging
• No versioning or audit trail for report updates

Related pages

• Cross-border product research

• Data cleaning pipeline

• Data report templates

• Official docs → docs.openclaw.ai

• Issues → GitHub Issues