memory-patterns
Persistent memory patterns for cross-session learning and context retention
Quellinformationen
- Repository
- ruvnet/agentic-flow
- Letzte Quellaktivität
- 4. Januar 2026 um 20:11
- Erkannte Sprache von SKILL.md
- Englisch
- Sterne
- 821
- Forks
- 178
Installationsoptionen
Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.
Quelldateien prüfen
Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.
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SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau- 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
Auf GitHub ansehen