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 agentmods add agents/a5c-ai/babysitter/qwengit 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/agents/a5c-ai/babysitter/qwen)<a href="https://agentmods.dev/agents/a5c-ai/babysitter/qwen"><img src="https://agentmods.dev/badge/agents/a5c-ai/babysitter/qwen.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00000 | $0.00511 |
| Opus 5 | $0.00000 | $0.00255 |
| Sonnet 5 | $0.00000 | $0.00102 |
| Haiku 4.5 | $0.00000 | $0.00051 |
Grade A, and why
qwen 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 6d 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
Qwen Code
@qwen-code/qwen-code is Alibaba's
coding CLI built on top of Gemini CLI, tuned for the Qwen3-Coder family of
models. adapters drives it via the qwen binary.
Install
adapters install qwen
Supported on macOS, Linux and Windows.
Authenticate
Qwen Code speaks the OpenAI-compatible API. The quickest path is DashScope:
export OPENAI_API_KEY=sk-...
export OPENAI_BASE_URL=https://dashscope-intl.aliyuncs.com/compatible-mode/v1
export OPENAI_MODEL=qwen3-coder-plus
Alternatively, run qwen interactively and use the built-in OAuth flow.
Example
import { createClient } from '@a5c-ai/adapters';
const client = createClient();
const run = client.run({
agent: 'qwen',
model: 'qwen3-coder-plus',
prompt: 'Summarize the public API in src/index.ts',
});
for await (const ev of run.events()) {
if (ev.type === 'text_delta') process.stdout.write(ev.delta);
}
Plugins
Plugin support: no. Use MCP servers for extensibility.
MCP Servers
adapters mcp install qwen <mcp-server>
adapters mcp list qwen
Registry: https://modelcontextprotocol.io
Notes
- Session files live under
~/.qwen/sessions(JSONL). - MCP servers are configured under
mcpServersin~/.qwen/settings.json. - Capabilities are set conservatively — thinking, JSON mode, and image input
default to
falsepending upstream confirmation. - Qwen Code 0.16.2 keeps the npm package unchanged. Upstream adds
.qwen/QWEN.local.mdproject-local context, thememory-leak-debugskill, background-agent concurrency limits, Token Plan cache control, a three-tier auto-compaction ladder, headless runaway-protection guardrails, startup--worktreesupport, and SDK fixes forcanUseTooltimeouts and packaged CLI chunks. The graph tracks these as catalog/runtime compatibility metadata; adapters does not yet expose a typed worktree option for Qwen launch.
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.
- 6d ago First seen · 69 lines · 0 tokens per session scan A cce2d7526020
qwen is an agent published in the GitHub repository a5c-ai/babysitter (1,772 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 511 tokens. 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 2026-08-30.
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design-author
Use after research is complete to draft the approach before any code is written. Drafts a 200-line design document covering current state, desired end state, patterns to follow, and decisions made. Resolves its own open questions autonomously, recording each as an explicit, auditable assumption in the design.
planner
Use after the structure is produced to create the tactical implementation plan. Translates each vertical slice in 7-structure.md into precise file-level steps with acceptance test mappings. The plan is a tactical artifact for the implementer — neither the structure nor the plan is human-reviewed (the design passed…
security-reviewer
Use when a security review is needed after implementation. Applies OWASP-style checks with fresh context. Critical findings are a hard gate — they block shipping until resolved. Example triggers — "security review", "check for vulnerabilities", "audit this code for security issues".
technical-writer
Use after implementation to review whether project documentation needs updating. Reads the diff and compares against existing docs to identify gaps and stale content. Produces a structured report — does not rewrite docs itself. Example triggers — "check if docs need updating", "documentation review", "are the docs…
verifier
Use when comprehensive verification checks need to run before completion. Runs all available checks (format, lint, type check, build, tests) in speed order and produces an evidence-based report. Example triggers — "run all checks", "verify the build", "pre-flight checks", "does everything pass".