Home › Skills › Reclaim disk space on your Mac
Data & APIs

Reclaim disk space on your Mac skill for OpenClaw

⬇ 2.3K downloads ★ 0 stars Version 1.0.1 Rank #6211 of 10,000+

What this skill does

Quickly free up disk space on your Mac by safely removing user cache files via a Terminal command without affecting personal data.

The Reclaim disk space on your Mac skill is part of the Data & APIs category — data and API skills that fetch, query, and work with external data sources. You can install it on its own or alongside other data & apis skills from the OpenClaw catalog.

The Reclaim disk space on your Mac skill is ranked #6211 by downloads in the OpenClaw skill catalog (2.3K total downloads, 0 stars). It belongs to the Data & APIs category alongside 945 other top-10000 skills.

How to install the Reclaim disk space on your Mac 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 reclaim-disk-space-on-your-mac 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 Reclaim disk space on your Mac skill with a single command:

openclaw skills add reclaim-disk-space-on-your-mac

This pulls reclaim-disk-space-on-your-mac from ClawHub and installs it into ~/.openclaw/skills/reclaim-disk-space-on-your-mac/. Restart the OpenClaw gateway afterwards so the new skill is discovered.

How to use the Reclaim disk space on your Mac skill

Once installed, the Reclaim disk space on your Mac 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 reclaim-disk-space-on-your-mac-1.0.1.zip directly from our S3 mirror.
  2. Unzip into ~/.openclaw/skills/reclaim-disk-space-on-your-mac/ (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 Reclaim disk space on your Mac?

Install Reclaim disk space on your Mac in the OpenClaw Easy desktop app by opening the Skills panel, searching for reclaim-disk-space-on-your-mac, and clicking Install. From a terminal you can run: openclaw skills add reclaim-disk-space-on-your-mac. Either way the skill is placed in ~/.openclaw/skills/reclaim-disk-space-on-your-mac/.

Is the Reclaim disk space on your Mac 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 Reclaim disk space on your Mac do?

Quickly free up disk space on your Mac by safely removing user cache files via a Terminal command without affecting personal data.

Related: more data & apis skills

If the Reclaim disk space on your Mac skill looks useful, you may also want to check out other data & apis 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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Install Reclaim disk space on your Mac and 10,000+ other OpenClaw skills in one click. Free, open-source, runs locally on macOS & Windows.

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