redis-development Claude Code Plugin
Claude Code PluginClaude CodeDatabaseDatabases & StorageAI Agents & AI App DevelopmentClaude Code Customization & WorkflowThe explanation below is AI-generated. Please verify it against the sources.
redis-development is a Claude Code plugin that bundles a set of agent skills covering Redis development practices. According to the README, it packages eight distinct skills spanning core data structures, connection handling, search and vector search, semantic caching, clustering, security, observability, and Redis Agent Memory (Iris). Each skill follows the Agent Skills specification, with a required SKILL.md instructions file and optional reference material, scripts, and assets. The skills can be installed through the Agent Skills CLI, as a Claude Code plugin, as a ChatGPT/Codex plugin package, or as a Cursor plugin, and they activate automatically when the agent detects a relevant task. The homepage source describes Redis broadly as a real-time data platform with caching, search, streaming, and AI-context features, but the plugin itself is scoped to development guidance rather than to any single hosted service.
About the service
Redis is a data platform, available both as open-source software and as managed cloud offerings, that provides caching, search and vector search, streaming, session management, and related capabilities; it also offers an agent-memory and context feature set (Iris) and a semantic cache feature (LangCache) referenced by some of the bundled skills.
What you can do with redis-development
- Get guidance on Redis data structures, key naming, memory/TTL handling, atomic operations, and choices like JSON vs Hash or Streams vs Pub/Sub
- Review connection handling topics such as pooling, multiplexing, pipelining, client-side caching, timeouts, and slow commands
- Build search and RAG-style pipelines with FT.CREATE schemas, FT.SEARCH/FT.AGGREGATE/FT.HYBRID, vector similarity indexing, hybrid retrieval, and zero-downtime index updates
- Set up semantic caching for LLM responses via LangCache, including similarity threshold tuning and per-task cache separation
- Address clustering concerns like hash tags, avoiding CROSSSLOT errors, and reading from replicas
- Apply security practices including authentication, TLS, ACL-based least privilege, network binding, firewalls, and command renaming
- Monitor and debug Redis using INFO metrics, SLOWLOG, MEMORY DOCTOR, FT.PROFILE, and Redis Insight
- Work with Iris (Redis Agent Memory) for provisioning, SDK authentication, session events, long-term memory search, and async promotion