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Redis Js

Official
upstash·vlatest·database·MIT

Connect to and manage Upstash Redis databases using JavaScript code directly within your AI workflows.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add upstash/redis-js --skill redis-js -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

upstash

Matched to the vendor's own GitHub organisation.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned upstash/redis-js at 6b27727530.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
6b27727530
Manifest
skills/SKILL.md
Scanned
32 files, 3,664 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The redis-js skill enables AI agents to interact directly with Upstash Redis, a serverless in-memory data store. It allows agents to perform real-time operations like storing and retrieving data, managing sessions, and caching results within JavaScript environments.

When to use it

  • Implementing fast, temporary session storage for user authentication flows.
  • Caching expensive API responses or database query results to reduce latency.
  • Managing real-time leaderboards or chat message histories in multiplayer applications.
  • Storing ephemeral data such as shopping cart contents or form drafts.

Key capabilities

  • Direct integration with the Upstash Redis serverless platform.
  • Full support for standard Redis commands via JavaScript.
  • Serverless architecture requiring no infrastructure management.
  • High-performance in-memory data access patterns.

Example prompts

  • "Set up a caching layer using redis-js to store the results of my weather API calls."
  • "Create a function to save user session tokens in Upstash Redis for 24 hours."
  • "Implement a real-time counter for active users on my dashboard using redis-js."

Tips & gotchas

Ensure your AI agent has valid credentials and the correct endpoint URL configured before attempting to connect. Since this is an in-memory store, data will be lost if the serverless instance scales down or is deleted, so do not rely on it for permanent data persistence.