research.mdā¢2.97 kB
# Research Swarm Strategy
## Purpose
Deep research through parallel information gathering.
## Activation
### Using MCP Tools
```javascript
// Initialize research swarm
mcp__claude-flow__swarm_init({
"topology": "mesh",
"maxAgents": 6,
"strategy": "adaptive"
})
// Orchestrate research task
mcp__claude-flow__task_orchestrate({
"task": "research topic X",
"strategy": "parallel",
"priority": "medium"
})
```
### Using CLI (Fallback)
`npx claude-flow swarm "research topic X" --strategy research`
## Agent Roles
### Agent Spawning with MCP
```javascript
// Spawn research agents
mcp__claude-flow__agent_spawn({
"type": "researcher",
"name": "Web Researcher",
"capabilities": ["web-search", "content-extraction", "source-validation"]
})
mcp__claude-flow__agent_spawn({
"type": "researcher",
"name": "Academic Researcher",
"capabilities": ["paper-analysis", "citation-tracking", "literature-review"]
})
mcp__claude-flow__agent_spawn({
"type": "analyst",
"name": "Data Analyst",
"capabilities": ["data-processing", "statistical-analysis", "visualization"]
})
mcp__claude-flow__agent_spawn({
"type": "documenter",
"name": "Report Writer",
"capabilities": ["synthesis", "technical-writing", "formatting"]
})
```
## Research Methods
### Information Gathering
```javascript
// Parallel information collection
mcp__claude-flow__parallel_execute({
"tasks": [
{ "id": "web-search", "command": "search recent publications" },
{ "id": "academic-search", "command": "search academic databases" },
{ "id": "data-collection", "command": "gather relevant datasets" }
]
})
// Store research findings
mcp__claude-flow__memory_usage({
"action": "store",
"key": "research-findings-" + Date.now(),
"value": JSON.stringify(findings),
"namespace": "research",
"ttl": 604800 // 7 days
})
```
### Analysis and Validation
```javascript
// Pattern recognition in findings
mcp__claude-flow__pattern_recognize({
"data": researchData,
"patterns": ["trend", "correlation", "outlier"]
})
// Cognitive analysis
mcp__claude-flow__cognitive_analyze({
"behavior": "research-synthesis"
})
// Cross-reference validation
mcp__claude-flow__quality_assess({
"target": "research-sources",
"criteria": ["credibility", "relevance", "recency"]
})
```
### Knowledge Management
```javascript
// Search existing knowledge
mcp__claude-flow__memory_search({
"pattern": "topic X",
"namespace": "research",
"limit": 20
})
// Create knowledge connections
mcp__claude-flow__neural_patterns({
"action": "learn",
"operation": "knowledge-graph",
"metadata": {
"topic": "X",
"connections": relatedTopics
}
})
```
### Reporting
```javascript
// Generate research report
mcp__claude-flow__workflow_execute({
"workflowId": "research-report-generation",
"params": {
"findings": findings,
"format": "comprehensive"
}
})
// Monitor progress
mcp__claude-flow__swarm_status({
"swarmId": "research-swarm"
})
```