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redis-core

提供 Redis 数据建模的两项核心指导：按访问模式选择 String、Hash、List、Set、Sorted Set、JSON、Stream 或 Vector Set，以及采用冒号分隔的分层键名规范；含反模式说明与 Python/Java 示例，属纯文档型参考，不含可执行代码或工具。

redis
热度 0.00
最近更新 2026-10-19 01:55:48
分类：开发依赖：纯提示词应用场景：概念解释 / 代码审查 / 推荐

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add redis/agent-skills/redis-core
Metadata
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
metadata
{"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_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