skills/babysit-pr/SKILL.md
--- name: babysit-pr description: Babysit a pull request through its bot review rounds: verify, fix, reply, resolve. Use for any babysit or watch-the-PR ask. category: AI & Agents source: antigravity tags: [node, api, ai, agent, gpt, document, security, rag, cro] url: https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/babysit-pr --- # Babysit a PR ## When to Use - A PR/MR has accumulated bot review threads that need verification, fixes, replies, and resolution. - You want
npx skillsauth add ranbot-ai/awesome-skills skills/babysit-prInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Goal: carry a pull request (GitHub) or merge request (GitLab) from "just opened" to "nothing left unanswered," without the human having to sit and refresh the page. "PR" below means either.
Review bots are diff-anchored samplers. Every push mints a fresh round, and a fix in one place can light up commentary somewhere adjacent. Left alone, a PR accumulates half-answered threads that nobody resolves, and the real bug in round three gets buried under nitpicks from rounds one and two. Your job is to be the person who reads every finding, decides what is actually true, fixes what blocks, and closes every loop in writing.
You know how to drive gh (GitHub), glab (GitLab), and git. What follows is only the judgment this
loop needs and the few API calls that are easy to get wrong. The harvest script picks the forge from
the cwd's git origin; everything it returns has the same shape on both, with a capabilities block
naming what that forge cannot tell you.
Verify before you believe. A bot's severity badge is a guess made without running anything. Treat every finding, including the P1s, as a claim to check against the code. Bots are frequently right (that is why this loop is worth running), and they are also confidently wrong often enough that shipping their suggestions unexamined will introduce bugs. Read the actual code path before you agree or disagree.
Every thread gets an answer. A finding you fixed, rejected, or deferred is only closed once you have said so in that thread and resolved it. Silence reads as "ignored" to the next human who opens the PR, and it is how a real bug gets lost.
Publish before you answer. A "fixed" reply is only true once the remote branch carries the fix. Never post a confirmed reply, or resolve its thread, while the fix exists only locally. Rejections need no push. Reply with evidence and resolve immediately.
Findings arrive on two different surfaces, and a round that reads only one silently misses half of them. This is the single most common way a babysit loop goes wrong:
thread_id (to resolve) and a reply_to (to reply inside the
thread). On GitHub these are GraphQL review threads; on GitLab they are discussions.The bundled script returns both in one call, already correlated (<skill-dir> is the folder that
holds this SKILL.md):
"<skill-dir>/scripts/threads.sh" <N> > /tmp/pr-<N>-round-<k>.json
Never trust a filtered count without its unfiltered twin. Before applying any jq filter to the
harvest, print the raw totals (jq '{threads: (.threads|length), reviews: (.reviews|length)}') and
compare. A filter that eliminates 100% of items is presumed broken until the field names are
verified against the actual schema (jq '.threads[0] | keys'). jq selects on a misspelled field
fail silently-empty, and a "clean round" built on one is how a P1 gets a merge-gate mention posted
over it. That has happened. GitHub tooling fails by returning less data, not by erroring; pair this with the
pagination rule.
Never describe an object you did not fetch. If a query for a specific id returns empty, that is a
stop signal. Say "I can't see it" and fetch it another way (gh api .../reviews/<id>), never narrate
its presumed content. Related trap: every inline thread reply arrives wrapped in a zero-byte
COMMENTED review object, so a watcher's "new review" event may be just a reply wrapper, not a new
round. threads.sh's .reviews does not include these wrappers, so a review id from an event that is
missing from the harvest means "wrapper", not "gone".
Diff it against the previous round's file to see what is genuinely new. outdated: true on a thread
means the line moved underneath it. The finding may already be fixed, so check it against current
code before spending the round on it. A comment_count bump on a thread you already handled means a
bot followed up inside it.
Has this reviewer seen the current push? Only trust a field that names a sha. On GitHub each review
carries commit_id; compare it to head. For debate-review on either forge, the round body's
debate_head is the sha it reviewed. On GitLab other reviewers' notes carry no sha (`capabilities.
re
tools
Delegate coding tasks to the Grok Build CLI only when the user explicitly requests it, while the orchestrator retains review and landing responsibility.
development
--- name: graceful-shutdown description: Implement graceful shutdown for servers and workers: drain connections, finish in-flight work, release resources, and exit cleanly on SIGTERM/SIGINT. category: AI & Agents source: antigravity tags: [python, typescript, node, api, claude, ai, template, docker, kubernetes] url: https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/graceful-shutdown --- # Graceful Shutdown ## Overview A skill for implementing graceful shutdown in server
development
--- name: falsify description: The scientific thinking protocol for AI agents. Use when facing complex, ambiguous, or high-stakes questions where guessing is costly: hypothesis → attempt to break it → evidence → calibrated co category: Creative & Media source: antigravity tags: [markdown, claude, ai, agent, llm, template, design, security, rag, cro] url: https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/falsify --- # Falsify — The Scientific Thinking Protocol > Think like
tools
Configure approved delegation lanes across installed implementer CLIs, including optional model and effort choices, then write global or project config only after explicit user approval.