Babysitter is a workflow engine for AI coding agents that enforces predefined steps, quality checks, human approvals, and decision records. It is used to coordinate complex, repeatable agent workflows across supported coding tools. The catalogue contains skills, agents, instructions, settings, a plugin, and an MCP integration for its workflow.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add a5c-ai/babysitter --skill autonomous-coding-engagementgit clone --depth 1 https://github.com/a5c-ai/babysitterWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/a5c-ai/babysitter/autonomous-coding-engagement)<a href="https://agentmods.dev/skills/a5c-ai/babysitter/autonomous-coding-engagement"><img src="https://agentmods.dev/badge/skills/a5c-ai/babysitter/autonomous-coding-engagement/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/a5c-ai/babysitter/autonomous-coding-engagement"><img src="https://agentmods.dev/badge/skills/a5c-ai/babysitter/autonomous-coding-engagement.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00034 | $0.00119 |
| Opus 5 | $0.00017 | $0.00060 |
| Sonnet 5 | $0.00007 | $0.00024 |
| Haiku 4.5 | $0.00003 | $0.00012 |
Grade A, and why
autonomous-coding-engagement scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Autonomous Coding Engagement Skill
Stub — implementation pending.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 15 lines · 34 tokens per session scan A 193f325bd25b
autonomous-coding-engagement is a skill published in the GitHub repository a5c-ai/babysitter (1,789 stars, last pushed 7d ago), licensed MIT. It adds 34 tokens to every session and 119 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
Other skills, from other repositories
goga-review-plan
Verify execution plan completeness and correctness.
goga-brainstorm
Pipeline orchestrator for brainstorming the cells architecture.
goga-define-challenge
Challenge the complete product definition before the PRD is generated.
goga-define-experience
Define the user experience required to achieve the established product goals and solve the identified problem.
goga-define-goals
Define the product outcomes that should be achieved by solving the identified problem for the relevant users.
goga-brainstorm-cell-assembly
Assembling CODEMANIFEST and .usages per cell, with final approval.