yolo

Run Babysitter autonomously with minimal manual interruption.

509 stars

Best use case

yolo is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Run Babysitter autonomously with minimal manual interruption.

Teams using yolo should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/yolo/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/plugins/babysitter-codex/skills/yolo/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/yolo/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How yolo Compares

Feature / AgentyoloStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Run Babysitter autonomously with minimal manual interruption.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# yolo

Load and use the installed `babysit` skill.

Resolve the request in `yolo` mode:

- treat everything after `$yolo` as the autonomous execution request
- follow the `babysit` skill contract while optimizing for minimal manual
  interruption
- using this means the user wants to run autonomously with minimal manual
  interruption, so optimize for that by skipping or minimizing any steps that
  would require user input or decision-making during the run
- do not create a separate command surface here; this skill only forwards into
  `babysit`