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/chemany/mente/babysit-prnpx skills add chemany/Mente --skill babysit-prgit clone --depth 1 https://github.com/chemany/MenteWrote 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/chemany/mente/babysit-pr)<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>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 | $0.00114 | $0.02943 |
| Opus 5 | $0.00057 | $0.01471 |
| Sonnet 5 | $0.00023 | $0.00589 |
| Haiku 4.5 | $0.00011 | $0.00294 |
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.
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.
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
- 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. - Run the watcher script to snapshot PR/review/CI state (or consume each streamed snapshot from
--watch). - Inspect the
actionslist in the JSON response. - If
diagnose_ci_failureis present, inspect failed run logs and classify the failure. - If the failure is likely caused by the current branch, patch code locally, commit, and push.
- If
process_review_commentis present, inspect surfaced review items and decide whether to address them. - 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.
- 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. - If the failure is likely flaky/unrelated and
retry_failed_checksis present, rerun failed jobs with--retry-failed-now. - If both actionable review feedback and
retry_failed_checksare 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. - 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. - After any push or rerun action, immediately return to step 1 and continue polling on the updated SHA/state.
- If you had been using
--watchbefore pausing to patch/commit/push, relaunch--watchyourself in the same turn immediately after the push (do not wait for the user to re-invoke the skill). - Repeat polling until
stop_pr_closedappears 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. - Maintain terminal/session ownership: while babysitting is active, keep consuming watcher output in the same turn; do not leave a detached
--watchprocess running and then end the turn as if monitoring were complete.
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.
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.
- 5d ago First seen · 188 lines · 114 tokens per session scan A c7e028c8afd5
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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