Agent-Skills.md

Agent Skills: Redis Memory Backend Skill

Redis backend for conversation state persistence and caching

UncategorizedID: a5c-ai/babysitter/redis-memory-backend

Repository

a5c-ai/babysitter
a5c-aiLicense: MIT
244

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pnpm dlx add-skill https://github.com/a5c-ai/babysitter/tree/HEAD/plugins/babysitter/skills/babysit/process/specializations/ai-agents-conversational/skills/redis-memory-backend

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plugins/babysitter/skills/babysit/process/specializations/ai-agents-conversational/skills/redis-memory-backend/SKILL.md

Skill Metadata

Name
redis-memory-backend
Description
Redis backend for conversation state persistence and caching

Redis Memory Backend Skill

Capabilities

  • Configure Redis for conversation state storage
  • Implement message history persistence
  • Set up Redis caching for LLM responses
  • Configure TTL-based memory expiration
  • Implement Redis Pub/Sub for real-time updates
  • Design efficient key schemas

Target Processes

  • conversational-memory-system
  • chatbot-design-implementation

Implementation Details

Core Components

  1. Message Store: RedisChatMessageHistory
  2. Cache: LLM response caching
  3. State Store: Conversation state persistence
  4. Pub/Sub: Real-time updates

Configuration Options

  • Redis connection settings
  • Key prefix configuration
  • TTL settings
  • Serialization format
  • Cluster configuration

Key Schema Patterns

  • session:{session_id}:messages
  • cache:llm:{prompt_hash}
  • state:{user_id}:{key}

Best Practices

  • Use appropriate data structures
  • Configure proper TTLs
  • Implement connection pooling
  • Monitor memory usage

Dependencies

  • redis
  • langchain-community (RedisChatMessageHistory)