Redis writes skills that guide an AI agent through Redis work, including choosing data structures and key naming for models like caching, counters and leaderboards, designing RediSearch indexes with hybrid lexical and vector retrieval, and semantic caching of LLM responses on Redis Cloud. Its skills also cover AI agent memory through the Iris Redis Agent Memory plane, security and ACL least-privilege setup, Redis Cluster hash tags and CROSSSLOT debugging, observability and incident triage, and client connection tuning.
Agent Skills
8 skills · 174 stars · MIT
Iris Development Iris is Redis's umbrella for AI-focused products.
Redis Clustering Redis Cluster and replication guidance covering hash tags for multi-key operations, avoiding CROS…
Redis Connections Redis client and connection guidance covering connection pooling, multiplexing, pipelining, clien…
Redis Core Core Redis modeling guidance — choose the right data structure (String, Hash, List, Set, Sorted S…
Redis Observability Redis observability guidance — which metrics to monitor (memory, connections, hit ratio, ops/sec,…
Redis Search Redis Search guidance covering FT.CREATE schema design, field type selection (TEXT, TAG, NUMERIC,…
Redis Security Redis security guidance covering authentication (requirepass and ACL users), TLS, ACL-based least…
Redis Semantic Cache Redis LangCache guidance for semantic caching of LLM responses on Redis Cloud — calling search/se…