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 writing-plansgit 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/writing-plans)<a href="https://agentmods.dev/skills/a5c-ai/babysitter/writing-plans"><img src="https://agentmods.dev/badge/skills/a5c-ai/babysitter/writing-plans/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/writing-plans"><img src="https://agentmods.dev/badge/skills/a5c-ai/babysitter/writing-plans.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 | $0.00033 | $0.00269 |
| Opus 5 | $0.00016 | $0.00134 |
| Sonnet 5 | $0.00007 | $0.00054 |
| Haiku 4.5 | $0.00003 | $0.00027 |
Grade A, and why
writing-plans 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 5d 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 you have specs/requirements for multi-step work
- Before any implementation begins
Task Structure
Each task follows: Write failing test -> Verify fail -> Implement minimal code -> Verify pass -> Commit
Plan Format
- Header: Goal, Architecture, Tech Stack
- Tasks with exact file paths and complete code
- TDD steps with expected output
- Task persistence via
.tasks.json
Execution Handoff
After plan is written, choose:
- Subagent-Driven - Fresh agent per task with two-stage review
- Batch Execution - Execute in batches with human checkpoints
Agents Used
- Process agents defined in
writing-plans.js
Tool Use
Invoke via babysitter process: methodologies/superpowers/writing-plans
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.
- 5d ago First seen · 39 lines · 33 tokens per session scan A c8091ca12229
writing-plans is a skill published in the GitHub repository a5c-ai/babysitter (1,783 stars, last pushed 4d ago), licensed MIT. It adds 33 tokens to every session and 269 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
test-driven-bug-fix
Defines reproduce-red-green-refactor bug fixes. Load when correcting a defect with a regression test.
implementing-slices
Defines test-first slice execution, commits, and review fixes. Load when an implementer executes 8-plan.md.
test-first-development
Defines acceptance tests as the implementation scope contract. Load before production code is written for a planned change.
team-fix
Runs the compressed bug-fix pipeline. Trigger on "run the bug-fix pipeline", "team-fix this bug", or "/team-fix" only; never infer pipeline intent from a plain bug-fix request.
team-implement
Executes and verifies implementation slices. Trigger on "implement this", "execute the plan", or "/team-implement" only; never infer the phase from a ready plan.
moai-workflow-tdd
Test-Driven Development workflow specialist using RED-GREEN-REFACTOR cycle for test-first software development. Use when developing new features from scratch or when behavior specification drives implementation.