Gather findings — search across research namespaces:
- mcp__claude-flow__memory_search namespace research for raw findings
- mcp__claude-flow__memory_search namespace research-sources for references
- mcp__claude-flow__agentdb_pattern-search for discovered patterns
- mcp__claude-flow__agentdb_context-synthesize for AI-assisted context building
Grade evidence — for each finding, assess:
- High: Multiple independent sources agree, directly observed, reproducible
- Medium: Single credible source, indirectly supported, plausible
- Low: Anecdotal, single unverified source, speculative
Resolve contradictions — when findings conflict:
- Identify the specific claim in tension
- Compare evidence quality
- Check recency (newer data may supersede)
- Note unresolved contradictions explicitly
Predict relevance — call mcp__claude-flow__neural_predict to score which findings are most relevant to the original goal
Structure report:
- Executive summary (2-3 sentences answering the original question)
- Key findings (ranked by evidence quality)
- Methodology (what sources were checked)
- Limitations (what wasn't checked, what remains uncertain)
- Recommendations (concrete next actions)
- References (source links and memory keys)
Store synthesis — call mcp__claude-flow__memory_store namespace research-synthesis with the full report

Output format

# [Research Topic] — Synthesis Report

## Summary
[2-3 sentence answer]

## Key Findings
1. [Finding] — Evidence: High/Medium/Low
2. [Finding] — Evidence: High/Medium/Low

## Contradictions
- [Claim A] vs [Claim B]: [resolution or "unresolved"]

## Recommendations
1. [Action] — because [reasoning]

## Sources
- [key]: [description]

research-synthesize

Research Synthesize

When to use

Steps