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
# 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
# Store decision with context
npx agentic-flow@alpha memory store \
"decisions:auth-method" \
'{"choice": "JWT", "reason": "stateless, scalable", "date": "2024-01-01"}'
Code Patterns
# Store reusable code pattern
npx agentic-flow@alpha memory store \
"patterns:error-handling" \
"try-catch with custom error classes and logging"
Learning Patterns
# Store learning from successful task
npx agentic-flow@alpha memory store \
"learnings:react-hooks" \
"useCallback for event handlers, useMemo for expensive computations"
MCP Tools
// 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
- Use namespaces: Organize by scope
- Be specific: Clear, searchable keys
- Include context: Store decisions with reasoning
- Clean up: Delete stale patterns
- Version patterns: Track changes over time
chat Comments (0)
Sign in to join the discussion and leave a comment.
Skill Details
GitHub Stars
526
GitHub Forks
123
Created
Mar 2026
Last Updated
4个月前
development
development architecture patterns
Related Skills
Build your own?
Join 12,000+ developers contributing to the Claude ecosystem.
No comments yet. Be the first to share your thoughts!