redis
Redis in-memory cache, pub/sub, streams, and data structures. Use for caching and real-time data.
Best use case
redis is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Redis in-memory cache, pub/sub, streams, and data structures. Use for caching and real-time data.
Teams using redis should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/redis/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How redis Compares
| Feature / Agent | redis | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Redis in-memory cache, pub/sub, streams, and data structures. Use for caching and real-time data.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Redis Redis (Remote Dictionary Server) is an in-memory data structure store, used as a database, cache, and message broker. It is incredibly fast. ## When to Use - **Caching**: The #1 use case. Cache HTML, JSON, or DB results. - **Session Store**: User sessions (speed + automatic expiry). - **Queues**: Simple background job queues using Lists (`LPUSH`/`RPOP`). - **Real-time**: Leaderboards, Counting, Pub/Sub. ## Quick Start ```bash # Set a value with 10 second expiry SET session:123 "active" EX 10 # Increment a counter atomically INCR page:views # Store a hash (object) HSET user:100 name "Jeevan" role "admin" ``` ## Core Concepts ### Single Threaded Redis uses a main single thread. Requests are processed sequentially, atomic by design. (Though I/O threading runs in background). ### Persistence (RDB vs AOF) - **RDB**: Snapshots every X minutes. Fast restart, potential data loss. - **AOF**: Logs every write. Slower, better durability. ### Data Structures Strings, Lists, Sets, Sorted Sets (`ZSET`), Hashes, Bitmaps, HyperLogLogs, Geospatial, Streams. ## Best Practices (2025) **Do**: - **Use Redis Stack**: Includes extensions like RediSearch (`FT.SEARCH`), RedisJSON, and Bloom Filters. - **Use Connection Pooling**: Opening connections is expensive. - **Set `maxmemory-policy`**: Configure what happens when RAM is full (e.g., `allkeys-lru` to delete old data). **Don't**: - **Don't use `KEYS *`**: It blocks the server scanning all keys. Use `SCAN`. - **Don't store huge values**: Redis is for small, fast data. ## References - [Redis Documentation](https://redis.io/docs/)
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