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Found 2 Skills
Implement multi-layer LLM caching with exact match, semantic similarity, and provider-side prompt caching. Reduce API costs by 30–70%, cut latency, and improve throughput using Redis, GPTCache, and provider caching APIs.
All-in-one Redis expertise covering data modeling and key naming, client connections (pooling, pipelining, client-side caching, timeouts), clustering and replication, Redis Search (FT.CREATE, vector and hybrid search, RAG pipelines), observability and incident triage, production security hardening, and semantic caching for LLM responses via LangCache. Use whenever designing, writing, reviewing, or debugging anything that touches Redis: choosing a data structure, naming keys, configuring a client, sharding across a cluster, building or tuning a search index, monitoring or diagnosing performance, hardening a deployment, or caching LLM completions. Adapted from Redis, Inc.'s official agent-skills repository (https://github.com/redis/agent-skills, MIT licensed), merged into one skill so the right domain loads automatically without picking between seven separate ones.