Babysitter

Code and enforce agent-workforce workflows with approval gates, quality checks, and replayable run records.

Stars
★ 1.8k
Last updated
23d ago
License
MIT
Primary language
JavaScript

At a glance

Works with
Universal · cross-platformClaude CodeCodex · Claude.ai (Partial support)
You'll need
Node.js 20.0.0+A supported AI coding harnessShell / CLINetwork accessLocal filesystemMCP Server
Typical use
An engineering lead who needs a delivery sequence such as plan, human approval, implementation, testing, and score-based refinement encoded and enforced in JavaScript.
Main limitation
The main CLI requires Node.js 20.0.0+, while the adapters CLI has a higher 20.9.0+ floor.

What does this agent do, and when should you use it?

Babysitter is a workflow-orchestration project for AI coding harnesses, exposed through the babysitter, genty, and adapters CLIs plus harness plugins. Its workflows are JavaScript processes that can call ctx.task and ctx.breakpoint, with the runtime using that process to determine which next task is permitted. Tasks, gates, and decisions are recorded in an event-sourced journal, enabling replay and interrupted-run resumption. Version 6 uses the Adapters runtime to run the same process across supported coding harnesses, while an internal harness can execute processes for scripts, tests, and CI/CD without an external coding agent. The repository also includes blueprints, a process library, configurable compression, MCP server startup, and genty runtime-management commands.

A user starts a run through in-session commands such as /babysitter:call, /babysitter:yolo, and /babysitter:plan, or with genty call --harness <harness> --prompt <prompt> --workspace <path>. In a JavaScript process, await ctx.task(...) dispatches work and await ctx.breakpoint(...) creates a required human gate; normal code conditions can use quality-check results to gate subsequent work. After each step, the runtime checks what the process permits next and records tasks, gates, and decisions under ~/.a5c/runs/ by default, with compatibility reads from repository-local .a5c/runs/. The genty CLI provides resume, doctor, retrospect, cleanup, and start-server; the internal harness can execute a process or prompt directly and delegate subtasks to discovered installed harnesses. Plugins automatically register four compression layers, configurable through BABYSITTER_COMPRESSION_ENABLED, babysitter compression:toggle, and .a5c/compression.config.json.

  1. An engineering lead who needs a delivery sequence such as plan, human approval, implementation, testing, and score-based refinement encoded and enforced in JavaScript.
  2. A CI/CD maintainer who wants to run a lint-and-test process through genty call --harness internal where no external coding-agent CLI is available.
  3. A Claude Code team that needs structured approval gates during a long-running task and wants to resume it with /babysitter:resume after interruption.
  4. An engineering group using Claude Code, Codex CLI, or other supported harnesses that wants to reuse one process through Adapters.
  5. A team that must audit and review automated runs using journal records together with genty doctor and genty retrospect.

How do you install or deploy this agent?

Prerequisites are Node.js 20.0.0+ (the adapters CLI requires 20.9.0+) and a supported AI coding harness. Install the main CLI:

npm install -g @a5c-ai/babysitter

To drive a harness directly from the shell, install:

npm install -g @a5c-ai/adapters-cli
adapters doctor

For runtime orchestration commands, install:

npm install -g @a5c-ai/genty-platform

For Claude Code, add the a5c-ai/babysitter marketplace and install [email protected]. For Codex CLI (Beta), run codex plugin marketplace add a5c-ai/babysitter. The supplied material does not document an additional credential-configuration step.

How do you use this agent?

In a Claude Code session, run:

/babysitter:user-install
/babysitter:project-install
/babysitter:doctor
/babysitter:call implement user authentication with TDD

A minimal runtime invocation is:
genty call --harness claude-code --prompt "implement user authentication with TDD" --workspace .

For automation without an external coding agent:

genty call --harness internal --process .a5c/processes/lint-and-test.js#process --workspace . --no-interactive --json

Resume an interrupted run with genty resume --run-id <runId> --harness claude-code --workspace .

What are this agent's strengths and limitations?

Pros
  • Workflows are executable JavaScript rather than prompt-only conventions: ctx.task, ctx.breakpoint, and code conditions can constrain subsequent work.
  • It records tasks, gates, and decisions in a journal designed for deterministic replay and resumption.
  • It offers in-session plugins, the host-side adapters CLI, the genty runtime CLI, and an internal harness for both interactive and headless use.
  • Structured human approvals, parallel dispatch, and quality gates provide governance mechanisms beyond a one-off task prompt.
Limitations
  • The main CLI requires Node.js 20.0.0+, while the adapters CLI has a higher 20.9.0+ floor.
  • Except for the internal harness, typical use depends on an installed supported AI coding harness, with installation differing by harness.
  • Codex CLI support is marked Beta; Cursor, Gemini CLI, GitHub Copilot, Pi, Hermes, Oh-My-Pi, OpenCode, and OpenClaw support are marked Experimental.
  • Adopting the full stack requires understanding separate package roles for @a5c-ai/babysitter, @a5c-ai/adapters-cli, @a5c-ai/genty-platform, and harness plugins.

How does this agent compare with similar options?

Key facts side by side with the most closely related agents.

Agent Source review Stars Updated Language Full support on
Babysitter This agent 52 · Major gaps ★ 1.8k 23d ago JavaScript Claude Code
Agency Orchestrator: One Sentence to Orchestrate an AI Expert Team 61 · Some gaps ★ 2.3k 1d ago TypeScript Codex · Claude Code · OpenAI API · Claude API
Dagu Workflow Orchestrator 74 · Some gaps ★ 4.1k 1d ago Go Codex · Claude Code · Claude API
DuraGraph 45 · Major gaps ★ 163 11d ago Go

How does FollowAgents rate this agent?

FollowAgents source review · FARS-2.1
Major gaps
52/ 100 5-point scale 2.6 / 5
Trust 11/29
Reliability 8/14
Adaptability 12/18
Convention 10/18
Effectiveness 7/13
Verifiability 4/8
Why each dimension lost points
Trust11 / 29 · 1.9/5

Evidence shows: README emphasizes mandatory stops, breakpoints (human approval), and immutable journal, indicating user confirmation mechanisms; but no specific implementation details for least privilege, data flow transparency, sensitive data handling, dependency security, external effects, rollback, or source attribution. Deductions: these aspects are only asserted or partially evidenced, not adequately handled.

Reliability8 / 14 · 2.9/5

Evidence shows: README and test files (e.g., bridge-hooks.test.ts) indicate error handling and fallback logic, but dependency availability is unverified, and failure messages are partially covered in tests. Deductions: dependency availability not confirmed, failure message coverage limited.

Adaptability12 / 18 · 3.3/5

Evidence shows: README describes multiple usage scenarios (interactive, autonomous, planning, continuous) and multiple harness support, capability boundaries defined via process code, trigger commands clear, environment fit has install matrix. Deductions: capability boundaries and trigger precision documented but not fully verified, environment fit depends on external harnesses.

Convention10 / 18 · 2.8/5

Evidence shows: README structure clear, install notes detailed, naming stable (package names and commands), examples and FAQ sections present, MIT license explicit. Deductions: known limitations not explicitly listed, versioning/changelog not provided, maintenance responsibility not clear.

Effectiveness7 / 13 · 2.7/5

Evidence shows: output usability has JSON output and CLI commands, marginal value has unique features (process enforcement, deterministic replay), but cost-benefit not quantified. Deductions: cost-benefit lacks data support.

Verifiability4 / 8 · 2.5/5

Evidence shows: claims in README partially supported by docs and tests, but cross-source corroboration insufficient, facts and inferences not clearly separated. Deductions: cross-source corroboration limited, facts and inferences mixed.

Risks and how to mitigate them
  • This repository is a large monorepo with multiple packages; static review may not cover all code paths.
  • Claims in README (e.g., 'deterministic, hallucination-free') require runtime verification, which static review cannot confirm.
  • Dependency security not fully assessed; recommend checking for dependency vulnerabilities.
  • Publisher identity unverified; treat with caution.
Evidence confidence: Low Reviewed Aug 09, 2026 Reviewed revision ca6e2eaa04a6 New commits since this review; the score may not cover them
See the full review method →

FAQ

Do I have to use Claude Code?
No. The material states that the v6 Adapters runtime runs the same process across 12 supported AI coding harnesses, and the internal harness needs no external AI coding agent.
Can a workflow continue before a human approves it?
That depends on the process code. ctx.breakpoint(...) is a structured gate described as blocking progression until satisfied, while yolo mode is documented as fully autonomous with no breakpoints.
Is run state lost after an interruption?
The project records tasks, gates, and decisions in an event-sourced journal intended for deterministic replay. Runs can be continued with /babysitter:resume or genty resume.
Are pricing or additional credentials documented?
The supplied material documents npm and harness-plugin installation, but does not state Babysitter pricing, subscription requirements, or an additional credential setup. Requirements of the chosen harness are not detailed there.
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