babysitter:yolo

Start babysitting in non-interactive mode — no user interaction or breakpoints, fully autonomous execution.

509 stars

Best use case

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

Start babysitting in non-interactive mode — no user interaction or breakpoints, fully autonomous execution.

Teams using babysitter: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/.codex/skills/babysitter/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 babysitter:yolo Compares

Feature / Agentbabysitter:yoloStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Start babysitting in non-interactive mode — no user interaction or breakpoints, fully autonomous execution.

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

# babysitter:yolo

Identical to `/babysitter:call` but runs in **non-interactive mode**:

- **Skip the interview phase** — parse intent directly from the user's prompt
- **Auto-approve all breakpoints** — never pause for human approval
- **No user questions** — proceed autonomously through the entire orchestration loop

## Workflow

1. Parse the initial prompt to extract intent, scope, and requirements
2. Research the repo structure to understand the codebase
3. Search the process library for relevant specializations/methodologies
4. Create the process .js file and inputs
5. Create the run:

```bash
babysitter run:create \
  --process-id <id> \
  --entry <path>#<export> \
  --inputs <inputs-file> \
  --prompt "$PROMPT" \
  --harness codex \
  --session-id "${CODEX_THREAD_ID:-$CODEX_SESSION_ID}" \
  --plugin-root "$CODEX_PLUGIN_ROOT" \
  --json
```

6. Iterate until completion — auto-resolve all breakpoints:

```bash
babysitter run:iterate .a5c/runs/<runId> --json --iteration <n>
```

For breakpoint effects, immediately post approval:
```bash
echo '{"approved":true,"response":"Auto-approved (yolo mode)"}' > tasks/<effectId>/output.json
babysitter task:post .a5c/runs/<runId> <effectId> --status ok --value tasks/<effectId>/output.json --json
```

7. When `completionProof` is emitted, return it wrapped in `<promise>PROOF</promise>`

## Key Difference from /babysitter:call

The ONLY difference is that breakpoints are auto-approved and no user questions are asked. The orchestration loop, effect handling, and result posting are identical.

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