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Rilix

Official

@rilixai · United States of America

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2Public Repos
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2Published Skills

Rilix builds Beaker, the autonomous AI engineer

🐙 GitHub ↗🌐 Website ↗🐤 @withbeaker ↗
Skills Distribution
DomainAI Models & ...AI Models & Machin.. (55%)Developer Tooling .. (30%)Data Systems & Dat.. (15%)

Agent Skills by Rilix

Showing 2 vetted skills indexed across 1 GitHub repositories.

rilixairilixai
5

beaker-setup

Configures Python repositories with Beaker integration contracts and validates hosted optimization setup.

Official
Advanced
rilixairilixai
5

beaker-usage

Launch, monitor, pull, and cancel hosted Beaker optimization runs via the beaker CLI.

Official
Advanced

Frequently Asked Questions About Rilix

FAQPage Schema
What tasks can I perform with Rilix's Beaker skills?▼

You can set up a Python repository with the Beaker Integration contract, connect labeled data and application execution, validate the setup, then launch agent optimization runs, choose GitHub branches and datasets, pass comparison models, monitor run status, download results, and cancel runs.

Who are the Beaker skills designed for?▼

They target developers and ML engineers who want to optimize agents against real labeled data inside their own Python repositories, using Beaker's hosted execution while keeping evaluation tooling isolated under .beaker and preserving production behavior.

How do I install and run a Beaker integration?▼

Use the beaker-setup skill to scaffold the integration contract in your Python repository, connect labeled data and application execution, and validate the setup. Then use beaker-usage to launch optimization runs, select branches or datasets, and manage runs.

What license and cost apply to the Beaker skills?▼

Both beaker-setup and beaker-usage are released under the MIT open-source license at version 0.6.1, permitting free use, modification, and distribution. The skills pair with Beaker SDK version 0.6.1 and Beaker's hosted execution environment.

What prerequisites do the Beaker skills require?▼

You need a Python repository, real labeled data, and application execution to connect during setup. Operating runs requires an already-configured Beaker integration, hosted required environment variables, and optionally a GitHub branch, dataset, and comparison models.