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Automation & Workflows

golang-popular-libraries skill for OpenClaw

⬇ 2K downloads ★ 0 stars Version 1.2.0 Rank #8078 of 10,000+

What this skill does

Recommends production-ready Golang libraries and frameworks. Apply when the user explicitly asks for library suggestions, wants to compare alternatives, needs to choose a library for a specific task, or when a new dependency is being added to the project.

The golang-popular-libraries skill is part of the Automation & Workflows category — automation and workflow skills that schedule, trigger, and orchestrate tasks. You can install it on its own or alongside other automation & workflows skills from the OpenClaw catalog.

The golang-popular-libraries skill is ranked #8078 by downloads in the OpenClaw skill catalog (2K total downloads, 0 stars). It belongs to the Automation & Workflows category alongside 999 other top-10000 skills.

How to install the golang-popular-libraries skill

The easiest path is via the OpenClaw Easy desktop app — one click, no terminal required:

  1. Download OpenClaw Easy for macOS or Windows (free, one-click installer, ~30 seconds).
  2. Open the in-app Skills panel.
  3. Search for golang-popular-libraries and click Install.
  4. The skill activates automatically when an incoming message matches its description.

Install from the command line

If you already run the OpenClaw CLI, add the golang-popular-libraries skill with a single command:

openclaw skills add golang-popular-libraries

This pulls golang-popular-libraries from ClawHub and installs it into ~/.openclaw/skills/golang-popular-libraries/. Restart the OpenClaw gateway afterwards so the new skill is discovered.

How to use the golang-popular-libraries skill

Once installed, the golang-popular-libraries skill activates on its own: when an incoming message on WhatsApp, Telegram, Slack, Discord, Feishu or Line matches the skill's description, your OpenClaw agent loads it and runs the workflow. You can also trigger it explicitly by describing the task in chat. No extra configuration is required after install.

Manual install (advanced)

If you prefer manual installation:

  1. Click the Download skill .zip button above to grab golang-popular-libraries-1.2.0.zip directly from our S3 mirror.
  2. Unzip into ~/.openclaw/skills/golang-popular-libraries/ (create the directory if it does not exist).
  3. Restart OpenClaw Easy (or the OpenClaw CLI gateway) so the new skill is discovered.

Frequently asked questions

How do I install golang-popular-libraries?

Install golang-popular-libraries in the OpenClaw Easy desktop app by opening the Skills panel, searching for golang-popular-libraries, and clicking Install. From a terminal you can run: openclaw skills add golang-popular-libraries. Either way the skill is placed in ~/.openclaw/skills/golang-popular-libraries/.

Is the golang-popular-libraries skill free?

Yes. It is free to download and run through ClawHub, with no account or payment required. Each skill is published by its own author under its own licence — see its ClawHub page for the licence and source.

What does golang-popular-libraries do?

Recommends production-ready Golang libraries and frameworks. Apply when the user explicitly asks for library suggestions, wants to compare alternatives, needs to choose a library for a specific task, or when a new dependency is being added to the project.

Related: more automation & workflows skills

If the golang-popular-libraries skill looks useful, you may also want to check out other automation & workflows skills in the OpenClaw catalog:

Skills in this catalog are community-contributed integrations published on ClawHub and distributed under their own open-source licences. Product and company names, and any third-party service a skill connects to, are trademarks of their respective owners; a listing here does not imply affiliation with, sponsorship by, or endorsement from them. This page does not distribute any third-party application. Rights holders can reach us at hello@openclaw-easy.com.

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Free, open-source · Apache-2.0 · Works with Claude, ChatGPT, Gemini, or local Ollama models