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research-synthesize

Turn research findings stored in memory into structured reports with evidence ratings, source references, and practical recommendations. Compare conflicting claims, identify unresolved questions, and explain limitations so accumulated research can support decisions and next steps.

OriginalShow the original description

Synthesize research findings from memory into structured reports with evidence grading, contradiction resolution, and actionable recommendations

AI rating90/ 100See how to install

Good for

  • Combine findings from several research sessions
  • Compare conflicting claims and their supporting evidence
  • Prepare a research brief with recommended next steps
  • Save a synthesis for future reference

Overview

What it does

Collects research findings saved in memory and turns them into a report that supports decisions and action. It searches findings, references, and previously discovered patterns, then rates evidence as high, medium, or low. When information conflicts, it compares the claims, evidence quality, and recency, and explicitly records contradictions that remain unresolved. It assesses relevance to the original goal and organizes the summary, key findings, methodology, limitations, recommendations, and sources.

When it helps

Use it after one or more rounds of deep-research when you need a coherent view of the results. It helps when growing research notes make conclusions hard to see, or when you want to separate well-supported information from speculation before deciding what to do next. The consolidated findings can also be consulted later.

Example requests

  • “Combine the research on this topic, rate the evidence, and summarize next actions.”
  • “Review the saved research and identify conflicting claims and unresolved issues.”

Notes

Uses accumulated research and tools such as ruflo-core memory search and storage, and AgentDB. Its role is to synthesize saved findings rather than conduct new research. The completed report is saved in research-synthesis.

This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.

Objective evaluation

AI rated this skill on four points using only the contents of its SKILL.md. Stars and popularity are not taken into account.

Clear instructionsIs it clear when to use it and what it does?
AGoodIt explicitly describes use after deep-research and synthesis into reports with evidence ratings.
Concrete stepsAre steps, inputs, outputs, and examples spelled out?
AGoodSearch locations, evidence criteria, contradiction checks, report structure, and the storage destination are specified.
SafetyAre sending data, deleting files, and running commands disclosed?
AGoodThe memory write is explicitly scoped to saving the completed report in research-synthesis.
Easy setupDoes it need few tools or API keys, and are they documented?
BPartly lackingIt requires ruflo-core memory features and AgentDB, but provides no connection or installation steps.

The total counts each point as A = 25, B = 15, C = 5. Rated by AI (OpenAI Codex) as of Oct 21, 2026. Treat it as a guide and read the original before installing.

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Files included (1)

  • SKILL.md2.8 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

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__plugin_ruflo-core_ruflo__memory_search namespace research for raw findings
    • mcp__plugin_ruflo-core_ruflo__memory_search namespace research-sources for references
    • mcp__plugin_ruflo-core_ruflo__agentdb_pattern-search for discovered patterns
    • mcp__plugin_ruflo-core_ruflo__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__plugin_ruflo-core_ruflo__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__plugin_ruflo-core_ruflo__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]

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