research-synthesize
Synthesize research findings from memory into structured reports with evidence grading, contradiction resolution, and actionable recommendations
Best for research teamsWorks with GitHubLow risk
⌘source
- author
@ruvnet- repo
- ruvnet/ruflo
- language
- TypeScript
★46kstars
5.1kforks
May 5, 2026
✦overview.md
Key Features
- ·Evidence grading (High/Medium/Low)
- ·Contradiction resolution
- ·Multi-source aggregation
- ·Actionable recommendations
- ·Support for report, brief, table formats
Use Cases
- →Summarize findings from multiple deep-research sessions
- →Create an evidence-graded report for a technical decision
- →Resolve conflicting information from different sources
- →Generate a quick brief on a research topic for stakeholders
Best for
- ✓research teams
- ✓technical decision-making
- ✓synthesis of multiple sources
Not ideal for
- !real-time data
- !single-source summaries
FAQs
name
research-synthesize
description
Synthesize research findings from memory into structured reports with evidence grading, contradiction resolution, and actionable recommendations
argument-hint:<topic> [--format report|brief|table]
allowed-tools:mcp__claude-flow__memory_search mcp__claude-flow__memory_search_unified mcp__claude-flow__memory_list mcp__claude-flow__memory_retrieve mcp__claude-flow__memory_store mcp__claude-flow__agentdb_context-synthesize mcp__claude-flow__agentdb_pattern-search mcp__claude-flow__neural_predict Bash Read Write
Research Synthesize
Synthesize accumulated research findings into actionable reports.
When to use
After running deep-research (one or multiple times), when you need to pull together findings from memory into a coherent synthesis with recommendations.
Steps
- Gather findings — search across research namespaces:
mcp__claude-flow__memory_searchnamespaceresearchfor raw findingsmcp__claude-flow__memory_searchnamespaceresearch-sourcesfor referencesmcp__claude-flow__agentdb_pattern-searchfor discovered patternsmcp__claude-flow__agentdb_context-synthesizefor 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
$install
1-click copynpx skills add ruvnet/ruflo --skill research-synthesizeSafety assessment
★
Clarity score
How clear and easy to understand the SKILL.md instructions are, rated from 1 to 5.
4/ 5
very goodClear and well structured, with only minor parts that might need a second read.
◎
Actionability score
How directly an agent can act on the SKILL.md instructions, rated from 1 to 5.
4/ 5
highMostly actionable with clear steps; only a few small gaps remain.