- name
- memory-patterns
- description
- Persistent memory patterns for cross-session learning and context retention
- version
- 1.0.0
- invocable
- true
- author
- agentic-flow
- capabilities
- ["memory_store","memory_retrieve","pattern_learning","context_management"]
# Memory Patterns Skill
Implement persistent memory patterns for AI agents using ReasoningBank.
## Quick Commands
```bash
# Store a pattern
npx agentic-flow@alpha memory store "api:auth" "OAuth2 with JWT"
# Retrieve a pattern
npx agentic-flow@alpha memory get "api:auth"
# Search patterns
npx agentic-flow@alpha memory search "authentication"
# List all patterns
npx agentic-flow@alpha memory list --namespace project
```
## Memory Namespaces
| Namespace | Purpose | TTL |
|-----------|---------|-----|
| `session` | Current session context | Until end |
| `project` | Project-specific learnings | Permanent |
| `user` | User preferences | Permanent |
| `swarm` | Swarm coordination state | Swarm lifetime |
| `cache` | Temporary cached data | 1 hour |
## Pattern Types
### Decision Patterns
```bash
# Store decision with context
npx agentic-flow@alpha memory store \
"decisions:auth-method" \
'{"choice": "JWT", "reason": "stateless, scalable", "date": "2024-01-01"}'
```
### Code Patterns
```bash
# Store reusable code pattern
npx agentic-flow@alpha memory store \
"patterns:error-handling" \
"try-catch with custom error classes and logging"
```
### Learning Patterns
```bash
# Store learning from successful task
npx agentic-flow@alpha memory store \
"learnings:react-hooks" \
"useCallback for event handlers, useMemo for expensive computations"
```
## MCP Tools
```javascript
// Store memory
mcp__claude-flow__memory_usage({
action: "store",
key: "project:architecture",
value: "microservices with event-driven communication",
namespace: "project"
})
// Retrieve memory
mcp__claude-flow__memory_usage({
action: "retrieve",
key: "project:architecture",
namespace: "project"
})
// Search memories
mcp__claude-flow__memory_search({
pattern: "auth*",
namespace: "project",
limit: 10
})
```
## ReasoningBank Integration
ReasoningBank provides:
- **150x faster** vector search with HNSW
- **Reflexion memory** for self-improvement
- **Skill library** for learned capabilities
- **Causal graphs** for decision tracking
## Best Practices
1. **Use namespaces**: Organize by scope
2. **Be specific**: Clear, searchable keys
3. **Include context**: Store decisions with reasoning
4. **Clean up**: Delete stale patterns
5. **Version patterns**: Track changes over time
Ver en GitHub