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 issue-trackinggit 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/issue-tracking)<a href="https://agentmods.dev/skills/a5c-ai/babysitter/issue-tracking"><img src="https://agentmods.dev/badge/skills/a5c-ai/babysitter/issue-tracking/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/issue-tracking"><img src="https://agentmods.dev/badge/skills/a5c-ai/babysitter/issue-tracking.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 | $0.00025 | $0.00294 |
| Opus 5.5 | $0.00010 | $0.00118 |
| Sonnet 5.5 | $0.00005 | $0.00059 |
| Haiku 4.5 | $0.00003 | $0.00029 |
Grade A, and why
issue-tracking 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 1mo 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
- Tracking bead progress and status
- Managing bead dependencies
- Collecting attribution data for agent evaluation
Bead Lifecycle
- Created: Bead defined with scope and acceptance criteria
- Assigned: Bead placed on agent's hook
- In Progress: Agent actively working (GUPP enforced)
- Review: Work complete, awaiting merge review
- Done: Merged and verified (
gt done) - Destroyed: Wisps only - cleaned up after landing
Attribution
All work carries persistent attribution:
- Which agent completed the bead
- Time taken and quality score
- Used for A/B testing agent configurations
- Feeds into agent evaluation and scoring
Tool Use
Used within convoy management and orchestrator processes.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 37 lines · 25 tokens per session scan A 363c87f590db
issue-tracking is a skill published in the GitHub repository a5c-ai/babysitter (1,857 stars, last pushed 1mo ago), licensed MIT. It adds 25 tokens to every session and 294 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-03.
Other skills, from other repositories
team-pr
Use for opening PRs only on explicit request. Never infer from passed verification. Includes project terms, evidence, and risk.
vigilante-issue-implementation-on-gradle-multi-project
Implement a GitHub issue end-to-end when Vigilante dispatches work for a watched Gradle multi-project repository. Use the provided worktree, respect repository instructions, comment on the issue as work progresses, and report failures back to GitHub.
agentic-jujutsu
Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination.
github-automation
GitHub workflow automation, PR management, issue tracking, and code review coordination. Integrates with GitHub Actions and repository management. Use when: PR creation, code review, issue management, release automation, workflow setup. Skip when: local-only changes, non-GitHub repositories.
moai-workflow-worktree
Git worktree management for parallel SPEC development with isolated workspaces, automatic branch registration, and seamless MoAI-ADK integration. Use when setting up parallel development environments.
moai-ref-git-workflow
Git workflow patterns, branch strategies, conventional commits, and PR templates reference for git operations. Agent-extending skill that amplifies manager-git expertise with production-grade git workflow patterns. NOT for: code implementation, testing, architecture design, documentation content.