Atlas / Skills / ruvnet / Research Synthesize

Research SynthesizeCAUTION

skills/ruvnet/research-synthesize

🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated

Verdict
CAUTION
Grade
B
Trust score
89 /100
Version
—
Hosts
—
License
MIT
Stars
73,288
01

Overview

🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated

Read from source at commit ef7d4f0535e5OBSERVED · 2026-09-26
02

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
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__plugin_ruflo-core_ruflo__memory_search mcp__plugin_ruflo-core_ruflo__memory_search_unified mcp__plugin_ruflo-core_ruflo__memory_list mcp__plugin_ruflo-core_ruflo__memory_retrieve mcp__plugin_ruflo-core_ruflo__memory_store mcp__plugin_ruflo-core_ruflo__agentdb_context-synthesize mcp__plugin_ruflo-core_ruflo__agentdb_pattern-search mcp__plugin_ruflo-core_ruflo__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__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]
```
03

Trust audit

CAUTIONgrade B · trust 89/100 Install with care. The audit found things worth knowing before you trust its output.

LayerWhat it checksResult
L0Provenance & inventoryWARN
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (4)

MEDIUMInventory / provenance · inv.symlink · CWE-1104
crates
crates
Why it matters. link not followed
MEDIUMInventory / provenance · inv.symlink · CWE-1104
plugin/agents
plugin/agents
Why it matters. link not followed
MEDIUMInventory / provenance · inv.symlink · CWE-1104
plugin/commands
plugin/commands
Why it matters. link not followed
MEDIUMInventory / provenance · inv.symlink · CWE-1104
plugin/skills
plugin/skills
Why it matters. link not followed

Gates applied: no_behavioural_pass.

Audited 2026-09-26 · audit v0.4.1 · source sha ef7d4f0535e5full audit observations/trust-audit/skill/ruvnet__research-synthesize.json · Report an issue / request a re-scan
04

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-09-26ef7d4f0535e5CAUTIONB89first audit
05

Questions

What does the Research Synthesize skill do?

🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated

Is Research Synthesize safe to install?

With care. The audit graded it B (89/100) and found 4 things worth knowing before you trust this skill, listed below with the exact line each was found on.

What can Research Synthesize access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

How current is this page?

The grade is for one exact copy of the source (ef7d4f0535e5), read on 2026-09-26. The repository is watched, and a new audit runs when it changes — this is the first audit.

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