---
name: research-synthesize-f9c25313ba8b
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

1. **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
2. **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
3. **Resolve contradictions** — when findings conflict:
   - Identify the specific claim in tension
   - Compare evidence quality
   - Check recency (newer data may supersede)
   - Note unresolved contradictions explicitly
4. **Predict relevance** — call `mcp__claude-flow__neural_predict` to score which findings are most relevant to the original goal
5. **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)
6. **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]
```


---
Source attribution: digitalcrest01
Original project: https://github.com/digitalcrest01/ruflow/blob/8f78f238e1775aedf7faa6026b5f20c9aa8cbd12/plugins/ruflo-goals/skills/research-synthesize/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2024-2026 ruvnet

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: digitalcrest01
Original project: https://github.com/digitalcrest01/ruflow/blob/8f78f238e1775aedf7faa6026b5f20c9aa8cbd12/plugins/ruflo-goals/skills/research-synthesize/SKILL.md
Attribution basis: Source repository record

Fields of work: Data & Analytics, Education & Research, Marketing
Roles: Data Analyst, Marketing Analyst, Researcher
Specialties: Specialty not specified
Tools: Bash, Read, Write, Mcp__Claude Flow__Agentdb_Context Synthesize, Mcp__Claude Flow__Agentdb_Pattern Search, Mcp__Claude Flow__Memory_List, Mcp__Claude Flow__Memory_Retrieve, Mcp__Claude Flow__Memory_Search, Mcp__Claude Flow__Memory_Search_Unified, Mcp__Claude Flow__Memory_Store, Mcp__Claude Flow__Neural_Predict
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 5c64e21de76867072e73cc6f988b750098098b47d4bea869e88820901facb52a