Open SWE is an open-source software factory that gives coding tasks to an asynchronous agent, which investigates repositories, changes code, validates the results, and delivers pull requests. Engineering teams use it to automate code changes, reviews, CI follow-up, and related repository work from dashboards and connected tools.
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 langchain-ai/open-swe --skill baby-sitgit clone --depth 1 https://github.com/langchain-ai/open-sweWrote 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/langchain-ai/open-swe/baby-sit)<a href="https://agentmods.dev/skills/langchain-ai/open-swe/baby-sit"><img src="https://agentmods.dev/badge/skills/langchain-ai/open-swe/baby-sit/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/langchain-ai/open-swe/baby-sit"><img src="https://agentmods.dev/badge/skills/langchain-ai/open-swe/baby-sit.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 | $0.00030 | $0.01165 |
| Opus 5 | $0.00015 | $0.00583 |
| Sonnet 5 | $0.00006 | $0.00233 |
| Haiku 4.5 | $0.00003 | $0.00117 |
Grade A, and why
baby-sit 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 11d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- aisa-twitter-post-engage — 86% identical, 98 lines differ
How it starts
The opening of the file, as written. The whole thing — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Baby-sit a pull request
Use this skill when the user invokes /baby-sit, asks in natural language to monitor, unblock, or fix CI on a pull request, or when a baby-sit failure wakeup invokes /baby-sit --continue.
Inputs
/baby-sit: infer the open PR from the current branch withgh pr view./baby-sit <PR URL|number>: monitor that PR in the thread's configured repository./baby-sit stop [PR URL|number]: stop its active watch./baby-sit --continue <PR URL>: process an automated failure wakeup; do not register a second watch.
Always resolve the target to a canonical https://github.com/<owner>/<repo>/pull/<number> URL.
Start or stop
- Read the repository's
AGENTS.mdand check the worktree before any possible code change. - Fetch fresh PR state with
gh pr viewand the complete attached check set withgh pr checks --json name,bucket,state,workflow,link. - On local/desktop runs, do not call
manage_baby_sit. Forstop, end the local workflow. Otherwise, when checks are pending, rungh pr checks <PR URL> --watch --interval 60with theexecutetool's timeout set to 3300 seconds, then re-fetch the complete PR and check state. This bounded foreground watch is the only allowed local polling loop. - For cloud
stop, callmanage_baby_sitwith actionstop, report the result in the source thread, and end. - If the PR is closed or all checks are already terminal and non-failing, report that no watch is needed.
- Otherwise, on cloud runs call
manage_baby_sitwith actionstart. The watch reacts immediately to failing GitHub webhooks and uses a deterministic 10-minute fallback that consumes no model tokens while state is unchanged. - If cloud checks are only pending, report the current state and end the run. Do not start a shell polling loop and do not call
schedule_thread_wakeup. - If checks fail, continue with failure diagnosis in this run. If the local watch times out while checks remain pending, report the timeout and latest complete check state.
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.
- 11d ago First seen · 56 lines · 30 tokens per session scan A a0802bec64e2
baby-sit is a skill published in the GitHub repository langchain-ai/open-swe (10,688 stars, last pushed today), licensed MIT. It adds 30 tokens to every session and 1,165 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 2026-08-30.
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