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/redis-memory-backend

Redis backend for conversation state persistence and caching

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babysitter
1.8k200 skills3 agents21 commands1 MCP
Install
$ npx -y skills add a5c-ai/babysitter --skill redis-memory-backend --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/redis-memory-backend

Context preview

The summary Claude sees to decide when to auto-load this skill.

Redis backend for conversation state persistence and caching

SKILL.md

redis-memory-backend.SKILL.md
name: redis-memory-backend
description: Redis backend for conversation state persistence and caching
allowed-tools:
  - Read
  - Write
  - Edit
  - Bash
  - Glob
  - Grep
graph:
  domains: [domain:software-engineering]
  specializations: [specialization:ai-agents-conversational]
  skillAreas: [skill-area:context-management, skill-area:caching-strategies]
  roles: [role:ml-engineer, role:backend-engineer]
  workflows: [workflow:feature-development, workflow:ml-model-lifecycle]

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)
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