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 context-engineeringgit 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/context-engineering)<a href="https://agentmods.dev/skills/a5c-ai/babysitter/context-engineering"><img src="https://agentmods.dev/badge/skills/a5c-ai/babysitter/context-engineering/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/context-engineering"><img src="https://agentmods.dev/badge/skills/a5c-ai/babysitter/context-engineering.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 | $0.00028 | $0.00515 |
| Opus 5.5 | $0.00011 | $0.00206 |
| Sonnet 5.5 | $0.00006 | $0.00103 |
| Haiku 4.5 | $0.00003 | $0.00052 |
Grade A, and why
context-engineering 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
- Load: architecture docs, active code files, test files, recent changes
- Skip: historical discussions, completed milestones, research notes
- Priority: implementation speed
Review Mode
- Load: code diff, coding standards, security rules, test coverage
- Skip: architecture docs, planning notes, research
- Priority: thoroughness and accuracy
Research Mode
- Load: requirements, existing patterns, external research, alternatives
- Skip: implementation details, test files, CI configs
- Priority: breadth of information
Dynamic Injection
- Detect project context automatically (language, framework, tools)
- Load relevant skills based on detected context
- Inject domain-specific patterns and conventions
- Adjust tool allowlists per context mode
Selective Loading
- Load only files relevant to the current task
- Use glob patterns to scope file reading
- Prioritize recently modified files
- Skip binary files and generated code
Strategic Compaction
- Monitor context token usage
- Suggest compression for resolved/completed items
- Archive to memory files (activeContext, patterns, progress)
- Pre-compaction state preservation
- Automated compaction triggers at token thresholds
Cross-Platform Detection
- Package manager: npm (package-lock.json), pnpm (pnpm-lock.yaml), yarn (yarn.lock), bun (bun.lockb)
- Language: TypeScript (tsconfig.json), Go (go.mod), Python (pyproject.toml), Java (pom.xml)
- Test runner: vitest, jest, pytest, go test
- CI/CD: GitHub Actions, Dockerfile, docker-compose
When to Use
- Session initialization (detect context)
- Before each phase (inject relevant context)
- Token budget warnings (strategic compaction)
- Mode transitions (dev to review to research)
Agents Used
- Used by all agents indirectly through context detection
context-engineeringagent for explicit compaction analysis
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 · 63 lines · 28 tokens per session scan A f5d2a9c6ef7c
context-engineering is a skill published in the GitHub repository a5c-ai/babysitter (1,860 stars, last pushed 1mo ago), licensed MIT. It adds 28 tokens to every session and 515 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
agentmail
Use your assigned AgentMail inbox to read email tasks, explicitly send or reply, and check delivery. Provided automatically by your inbox assignment.
tutti-agent-workspace-app
Build or evolve a complex agent-enabled Tutti workspace app repository. Use for Tutti apps with web/server/shared monorepos, @tutti-os/agent-acp-kit local agent runtimes, kit-owned TUTTICLI agent/composer discovery, dynamic agent catalogs, run-scoped MCP tool gateways, app-owned package builders, web-first debugging…
daw-cli
Instructs agents to control Stratawright DAW via the daw-cli command-line IPC interface. Covers session state, transport, track management, gain staging, VST3/AU plugin hosting, signal routing, clips, MIDI timeline editing, and non-visual DSP analysis & audio intelligence. Requires the DAW application to be running.
kb-setup
Set up, initialize, or configure the local markdown knowledge base for a project. Use when the user says "set up the knowledge base", "init the KB", "configure the markdown KB", "index my docs", "add a doc source to the KB", or wants the project's markdown searchable by kb search. Wraps kb init end-to-end through kb…
goga-define-goals
Define the product outcomes that should be achieved by solving the identified problem for the relevant users.
goga-prototype-contracts
Designing usages and annotations per cell for the prototype pipeline.