babysit-pr

babysit-pr is a skill for Claude Code, Codex from chemany/Mente. It costs 114 tokens per session (2,943 once invoked), scanned A, original, MIT.

A continuous monitor for a GitHub pull request that checks reviews, automated tests, and whether it can be merged.

In plain words
What is it for?
It helps watch the pull request until it is merged, closed, or needs human help; diagnose failures, retry likely temporary failures, and fix suitable branch issues.
Why use it?
It prevents pending comments or failed checks from being missed after the pull request is created.

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/chemany/mente/babysit-pr
Any agent
npx skills add chemany/Mente --skill babysit-pr
Clone the repo
git clone --depth 1 https://github.com/chemany/Mente

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for babysit-pr

README.md
[![agentmods](https://agentmods.dev/badge/skills/chemany/mente/babysit-pr.svg)](https://agentmods.dev/skills/chemany/mente/babysit-pr)
Your own site
<a href="https://agentmods.dev/skills/chemany/mente/babysit-pr"><img src="https://agentmods.dev/badge/skills/chemany/mente/babysit-pr.svg" alt="Measured on agentmods" height="20"></a>
Per session 114 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,943 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 $0.02943
Opus 5 $0.00057 $0.01471
Sonnet 5 $0.00023 $0.00589
Haiku 4.5 $0.00011 $0.00294

Measured 5d ago against content hash c7e028c8afd5, 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 5d ago.

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.

kernel/codex/upstream/.codex/skills/babysit-pr/SKILL.md · 188 lines

How it starts

The opening of the file, as written. The whole thing — 188 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.
  6. If process_review_comment is present, inspect surfaced review items and decide whether to address them.
  7. If a review item is actionable and correct, patch code locally, commit, push, and then mark the associated review thread/comment as resolved once the fix is on GitHub.
  8. If a review item from another author is non-actionable, already addressed, or not valid, post one reply on the comment/thread explaining that decision (for example answering the question or explaining why no change is needed). Prefix the GitHub reply body with [codex] so it is clear the response is automated. If the watcher later surfaces your own reply, treat that self-authored item as already handled and do not reply again.
  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 · 188 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. 5d ago First seen · 188 lines · 114 tokens per session scan A c7e028c8afd5

Subscribe to this mod's changes

babysit-pr is a skill published in the GitHub repository chemany/Mente (11 stars, last pushed 3mo ago), licensed MIT. It adds 114 tokens to every session and 2,943 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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