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Research & Knowledge

Discovery skill for OpenClaw

⬇ 4.7K downloads ★ 0 stars Version 0.2.182 Rank #1535 of 10,000+

What this skill does

Automatically discover novel, statistically validated patterns in tabular data. Find insights you'd otherwise miss, far faster and cheaper than doing it yourself (or prompting an agent to do it). Disco systematically searches for feature interactions, subgroup effects, and conditional relationships you wouldn't think to look for, validates each on hold-out data with FDR-corrected p-values, and checks every finding against academic literature for novelty. Returns structured patterns with conditions, effect sizes, citations, and novelty scores.

The Discovery skill is part of the Research & Knowledge category — research and knowledge skills that gather, search, and summarize information. You can install it on its own or alongside other research & knowledge skills from the OpenClaw catalog.

The Discovery skill is ranked #1535 by downloads in the OpenClaw skill catalog (4.7K total downloads, 0 stars). It belongs to the Research & Knowledge category alongside 1884 other top-10000 skills.

How to install the Discovery 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 discovery-engine 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 Discovery skill with a single command:

openclaw skills add discovery-engine

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

How to use the Discovery skill

Once installed, the Discovery 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 discovery-engine-0.2.182.zip directly from our S3 mirror.
  2. Unzip into ~/.openclaw/skills/discovery-engine/ (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 Discovery?

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

Is the Discovery 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 Discovery do?

Automatically discover novel, statistically validated patterns in tabular data. Find insights you'd otherwise miss, far faster and cheaper than doing it yourself (or prompting an agent to do it).

Related: more research & knowledge skills

If the Discovery skill looks useful, you may also want to check out other research & knowledge 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