babysit-pr

A watcher for a GitHub pull request, a proposed code change that is reviewed before being merged. It repeatedly checks reviews, automated tests, workflow runs, and whether the change can be merged.

In plain words
What is it for?
It diagnoses failed automated checks, retries likely temporary failures up to three times, and can fix and push suitable branch-related issues.
Why use it?
It reduces the need to check the pull request manually and keeps monitoring until it is merged, closed, or needs the user's help.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/openai/codex/babysit-pr
Any agent
npx skills add openai/codex --skill babysit-pr
Clone the repo
git clone --depth 1 https://github.com/openai/codex

Made for: Claude Code, Codex.

Per session 114 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,602 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00114 $0.03602
Opus 5 $0.00057 $0.01801
Sonnet 5 $0.00023 $0.00720
Haiku 4.5 $0.00011 $0.00360

Measured yesterday against content hash 8e4b149a345e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 yesterday.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/gh_pr_watch.py, scripts/test_gh_pr_watch.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Origin

Copies of this mod

7 near-identical copies found in the catalogue:

.codex/skills/babysit-pr/SKILL.md · 224 lines

How it starts

The opening of the file, as written. The whole thing — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PR Babysitter

Objective

Babysit a PR persistently until one of these terminal outcomes occurs:

  • The PR is merged or closed.
  • A situation requires user help (for example CI infrastructure issues, repeated flaky failures after retry budget is exhausted, permission problems, or ambiguity that cannot be resolved safely).
  • Optional handoff milestone: the PR is currently green + mergeable + review-clean. Treat this as a progress state, not a watcher stop, so late-arriving review comments are still surfaced promptly while the PR remains open.

Do not stop merely because a single snapshot returns idle while checks are still pending.

Inputs

Accept any of the following:

  • No PR argument: infer the PR from the current branch (--pr auto)
  • PR number
  • PR URL

Core Workflow

  1. When the user asks to "monitor"/"watch"/"babysit" a PR, start with the watcher's continuous mode (--watch) unless you are intentionally doing a one-shot diagnostic snapshot.
  2. Run the watcher script to snapshot PR/review/CI state (or consume each streamed snapshot from --watch).
  3. Inspect the actions list in the JSON response.
  4. If diagnose_ci_failure is present, inspect failed run logs and classify the failure.
  5. If the failure is likely caused by the current branch, patch code locally, commit, and push. Do not patch random flaky tests, CI infrastructure, dependency outages, runner issues, or other failures that are unrelated to the branch.
  6. If process_review_comment is present, inspect surfaced published review items and decide whether to address them.
  7. If a review item is actionable and correct, patch code locally, commit, push, and then resolve the associated review thread only when allowed by the GitHub state mutation policy below.
  8. Do not post replies to human-authored review comments/threads unless the user explicitly confirms the exact response. If a human review item is non-actionable, already addressed, or not valid, surface the item and recommended response to the user instead of replying on GitHub.
  9. If the failure is likely flaky/unrelated and retry_failed_checks is present, rerun failed jobs with --retry-failed-now.
  10. If both actionable review feedback and retry_failed_checks are present, prioritize review feedback first; a new commit will retrigger CI, so avoid rerunning flaky checks on the old SHA unless you intentionally defer the review change.
  11. On every loop, look for newly surfaced review feedback before acting on CI failures or mergeability state, then verify mergeability / merge-conflict status (for example via gh pr view) alongside CI.
  12. After any push or rerun action, immediately return to step 1 and continue polling on the updated SHA/state.
  13. If you had been using --watch before pausing to patch/commit/push, relaunch --watch yourself in the same turn immediately after the push (do not wait for the user to re-invoke the skill).
  14. Repeat polling until stop_pr_closed appears or a user-help-required blocker is reached. A green + review-clean + mergeable PR is a progress milestone, not a reason to stop the watcher while the PR is still open.
  15. Maintain terminal/session ownership: while babysitting is active, keep consuming watcher output in the same turn; do not leave a detached --watch process running and then end the turn as if monitoring were complete.

Read the full file on GitHub · 224 lines

Files

What ships with it

5 files 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.

Changes

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.

  1. yesterday First seen · 224 lines · 114 tokens per session scan A 8e4b149a345e

Subscribe to this mod's changes

babysit-pr is a skill published in the GitHub repository openai/codex (120,598 stars, last pushed today), licensed Apache-2.0. It adds 114 tokens to every session and 3,602 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 2026-08-30.

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