Decision Trees skill for OpenClaw

What this skill does

Decision tree analysis for complex decision-making across all domains. Use when user needs to evaluate multiple options with uncertain outcomes, assess risk/reward scenarios, or structure choices systematically. Applicable to business, investment, personal decisions, operations, career choices, product strategy, and any situation requiring structured evaluation. Triggers include decision tree, should I, what if, evaluate options, compare alternatives, risk analysis.

The Decision Trees 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.

How to install the Decision Trees 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 decision-trees 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 Decision Trees skill with a single command:

openclaw skills add decision-trees

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

How to use the Decision Trees skill

Once installed, the Decision Trees 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 decision-trees-1.0.1.zip directly from our S3 mirror.
2. Unzip into ~/.openclaw/skills/decision-trees/ (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 Decision Trees?

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

Is the Decision Trees 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 Decision Trees do?

Decision tree analysis for complex decision-making across all domains. Use when user needs to evaluate multiple options with uncertain outcomes, assess risk/reward scenarios, or structure choices systematically.

Related: more automation & workflows skills

If the Decision Trees skill looks useful, you may also want to check out other automation & workflows skills in the OpenClaw catalog:

• Uptime Kuma ⬇ 5.2K
• vmware-vks ⬇ 5.2K
• Voice ⬇ 5.1K
• Scrapling Web Scraping ⬇ 5.1K
• Midscene Automations Skills for Computer ⬇ 5.1K

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.

Browse the full OpenClaw skill catalog

This page covers just one skill. The OpenClaw skill hub has 10,000+ more — search, sort by downloads or stars, and install any of them in one click. There is also a curated awesome-openclaw-skills list grouped by use case.