redis-memory-backend
Redis backend for conversation state persistence and caching
npx skills add a5c-ai/babysitter --skill redis-memory-backend --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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)
- Capabilities
- Target Processes
- Implementation Details
- Core Components
- Configuration Options
- Key Schema Patterns
- Best Practices
- Dependencies
What does the redis-memory-backend skill do?
Redis backend for conversation state persistence and caching
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill redis-memory-backend --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.