Redis Core

redis-core

Core Redis modeling guidance — choose the right data structure (String, Hash, List, Set, Sorted Set, JSON, Stream, Vector Set) and use consistent colon-separated key names. Use when designing a Redis data model, caching objects, deciding between Hash and JSON, building counters, leaderboards, membership sets, or session stores, or when reviewing/cleaning up Redis key naming.

redis/agent-skills·3.4Kinstalls165stars

SKILL.md

Full skill instructions

Redis Core

Foundational guidance for modeling data in Redis. Covers data-type selection and key-name conventions — the two decisions that most directly drive memory, performance, and maintainability.

When to apply

Caching objects, sessions, or per-user state.
Counters, leaderboards, recent-items lists, unique-membership sets.
Reviewing or refactoring Redis key names.
Deciding between a Redis Hash and a JSON document for an entity.

1. Choose the right data structure

Pick the type that matches the access pattern, not just the shape of the data.

Use case	Recommended type	Why
Simple values, counters	String	Atomic `INCR`/`DECR`, `SET`/`GET`
Object with independently updated fields	Hash	Per-field reads/writes, no whole-object rewrite
Queue, recent-N items	List	O(1) push/pop at ends
Unique items, membership checks	Set	O(1) `SADD`/`SISMEMBER`/`SCARD`
Rankings, score-based ranges	Sorted Set	Score-ordered; `ZADD`/`ZRANGE`/`ZRANK`
Nested / hierarchical data	JSON	Path-level updates, nested arrays, RQE indexing
Event log, fan-out messaging	Stream	Persistent, consumer groups
Vector similarity	Vector Set	Native vector storage with HNSW

Common anti-pattern: stuffing a flat object into a serialized string. Updating one field means fetch + parse + mutate + rewrite. Use a Hash instead.

See references/choose-data-structure.md for full rationale and Python/Java examples.

2. Use consistent key names

Use colon-separated segments with a stable hierarchy:

{entity}:{id}:{attribute}
user:1001:profile
user:1001:settings
order:2024:items
session:abc123
article:987:likes
game:space-invaders:leaderboard

Rules of thumb:

Lowercase, colon-separated. No spaces, no mixed casing (User_1001_Profile is bad).
Keep keys short but readable — keys live in memory and appear in every command.
Don't use full URLs or long strings as keys. Extract a short identifier, or use a hash digest of the URL.
Prefix for multi-tenancy (tenant:42:user:7:cart) so scans and ACLs can target a tenant cleanly.
Be consistent. Pick one convention per service and apply it across all keys.

See references/key-naming.md for cleanup examples and edge cases.

References

Install skill

Copy and run in your terminal

npx -y skills add https://github.com/redis/agent-skills --skill redis-core

View on GitHub

redis-core

redis-connections
Redis client and connection guidance covering connection pooling, multiplexing, pipelining, client-side caching with RESP3, avoiding slow commands (KEYS, SMEMBERS, HGETALL), and tuning socket timeouts. Use when configuring a Redis client (redis-py, Jedis, Lettuce, NRedisStack), batching commands for throughput, eliminating per-request connection creation, iterating large keyspaces with SCAN, enabling client-side caching for read-heavy workloads, or setting connect and read timeouts.
2.4K installs
redis-security
Redis security guidance covering authentication (requirepass and ACL users), TLS, ACL-based least-privilege access control, restricting network exposure via bind and protected-mode, firewall rules, and disabling dangerous commands. Use when deploying Redis to production, defining ACL users for an application, configuring TLS connections, locking down a Redis instance behind a firewall, or auditing a Redis deployment for security hardening.
2.1K installs
redis-observability
Redis observability guidance — which metrics to monitor (memory, connections, hit ratio, ops/sec, rejected connections), which built-in commands to reach for during incident triage (SLOWLOG, INFO, MEMORY DOCTOR, CLIENT LIST, FT.PROFILE), and when to use the Redis Insight GUI. Use when setting up monitoring or alerts for a Redis instance, diagnosing a performance regression, profiling a slow FT.SEARCH query, or wiring Redis metrics into Prometheus, Datadog, or similar.
2K installs
redis-semantic-cache
Redis LangCache guidance for semantic caching of LLM responses on Redis Cloud — calling search/set via the SDK or REST API, tuning the similarity threshold, separating caches per task type, and filtering with custom attributes. Use when caching LLM completions or RAG answers to cut API cost and latency, building a cache-aside layer in front of OpenAI / Anthropic / etc., tuning hit rate vs precision, or splitting one app's LLM workloads into multiple LangCache caches.
1.7K installs

More skills from redis

redis/agent-skills

redis-clustering

Redis Cluster and replication guidance covering hash tags for multi-key operations, avoiding CROSSSLOT errors, and reading from replicas to scale read-heavy workloads. Use when designing keys for a sharded Redis Cluster, debugging CROSSSLOT errors on MGET / SDIFF / pipelines, configuring a multi-key transaction in a cluster, or routing reads to replicas for caches, analytics, or dashboards.

165 1.6K

View

redis/agent-skills

iris-development

Iris is Redis's umbrella for AI-focused products. Use this skill when integrating with the Iris Redis Agent Memory (RAM) data plane on Redis Cloud — recording session events for an AI agent, creating or searching long-term memories, configuring a memory store, or tuning background memory promotion. Code examples use the official `redis-agent-memory` (Python) and `@redis-iris/agent-memory` (TypeScript) SDKs.

165 1.5K

View