redis/redis-core
skills/redis-core/SKILL.md
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.
$ install --global
skillsauthnpx skillsauth add redis/agent-skills redis-coreInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- redis-core
- description:
- 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.
- license:
- MIT
- author:
- Redis, Inc.
- version:
- 0.1.0
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_Profileis 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
- Redis: Choosing the right data type
- Redis: Keys
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