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 skills/wibias/github-delivery/babysit-prnpx skills add Wibias/github-delivery --skill babysit-prgit clone --depth 1 https://github.com/Wibias/github-deliveryWrote 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/wibias/github-delivery/babysit-pr)<a href="https://agentmods.dev/skills/wibias/github-delivery/babysit-pr"><img src="https://agentmods.dev/badge/skills/wibias/github-delivery/babysit-pr.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 | $0.00113 | $0.00559 |
| Opus 5 | $0.00056 | $0.00280 |
| Sonnet 5 | $0.00023 | $0.00112 |
| Haiku 4.5 | $0.00011 | $0.00056 |
Grade A, and why
babysit-pr 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 3d 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
babysit-pr → github-delivery
OpenAI’s optional babysit-pr skill (npx skills add … --skill babysit-pr,
or repo-local .codex/skills/babysit-pr) polls CI/reviews via gh_pr_watch.py.
It is useful tooling, but it is not this user’s full ship loop (wake gate,
merge-ready bar, issue thanks, research/create).
If both are installed, prefer this redirect + github-delivery.
Do this instead
-
Load skill
github-delivery(~/.agents/skills/github-deliveryor~/.cursor/skills/github-delivery). -
Load
github-deliverySKILL.mdand the matching workflow (policy modules are declared in the workflow):- Default for babysit/watch/monitor →
references/watch-pr.md - If they asked merge-ready →
references/fix-pr-bots.md
- Default for babysit/watch/monitor →
-
First command every wake (watch):
node "<github-delivery>/scripts/watch-wake-gate.mjs" OWNER/REPO NExit
1→ triage OWNER/MEMBER comments in code (rebase/drop overlap / keep leftovers); resolve DIRTY conflicts. ACK-only does not clear. Never report waiting on CI/CodeRabbit while exit1. -
Ordering: reviews/owners → tip update → CI. Never merge-base-then-idle.
-
Optional: you may still use
gh_pr_watch.pyas a snapshot helper if present, but decisions and owner triage follow github-delivery — the Python watcher is not the policy engine.
Do not
- Treat green + mergeable from babysit-pr as full merge-ready (no own bug/security/spec, no settle, no issue notify).
- Idle on CI/CodeRabbit while
watch-wake-gate.mjsexits1. - Skip github-delivery merge ceremony (issue author thanks) when asked to merge.
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.
- 3d ago First seen · 42 lines · 113 tokens per session scan A 7dfa00604d8c
babysit-pr is a skill published in the GitHub repository Wibias/github-delivery (5 stars, last pushed 3d ago), licensed MIT. It adds 113 tokens to every session and 559 once invoked, about $0.0006 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 2026-08-31.
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