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 work-decompositiongit 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/work-decomposition)<a href="https://agentmods.dev/skills/a5c-ai/babysitter/work-decomposition"><img src="https://agentmods.dev/badge/skills/a5c-ai/babysitter/work-decomposition/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/work-decomposition"><img src="https://agentmods.dev/badge/skills/a5c-ai/babysitter/work-decomposition.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 | $0.00032 | $0.00327 |
| Opus 5 | $0.00016 | $0.00163 |
| Sonnet 5 | $0.00006 | $0.00065 |
| Haiku 4.5 | $0.00003 | $0.00033 |
Grade A, and why
work-decomposition 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 9d 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
- When a goal is too large for a single agent
- When parallel execution would benefit progress
- When work needs tracked attribution
Process
- Analyze the goal and project context
- Identify natural seams for decomposition
- Create MEOWs with clear boundaries and dependencies
- Classify as beads (persistent) or wisps (ephemeral)
- Map dependencies between MEOWs
- Estimate effort and assign priorities
Decomposition Principles
- Each MEOW should be completable by a single agent
- Dependencies should form a DAG (no cycles)
- Prefer more smaller beads over fewer larger ones
- Wisps for throwaway work (scaffolding, exploration)
- Every MEOW gets attribution tracking
Tool Use
Invoke via babysitter process: methodologies/gastown/gastown-orchestrator (analyze-work step)
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.
- 9d ago First seen · 37 lines · 32 tokens per session scan A 184cc8a30dea
work-decomposition is a skill published in the GitHub repository a5c-ai/babysitter (1,788 stars, last pushed 7d ago), licensed MIT. It adds 32 tokens to every session and 327 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 2026-09-03.
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Breaks a reviewed design into verified slices. Trigger on "slice this up", "break the design into steps", or "/team-structure".
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Defines tracker status transitions and closing rules. Load when a pipeline run is linked to a ticket.
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Bounded watch-loop mechanics for the pr-watch skills: cycle timing, soft cap, handoff. Load when running or authoring a PR watch loop.
team-question
Decomposes a feature into task and question artifacts. Trigger on "shape this idea", "decompose this task", or "/team-question".