Borrowing it
Nothing to install: this file belongs to Indemnity83/logistics. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Indemnity83/logistics/mc/26.2/.claude/skills/ship-pr-queue/SKILL.mdgit clone --depth 1 https://github.com/Indemnity83/logisticsWrote 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/indemnity83/logistics/ship-pr-queue)<a href="https://agentmods.dev/skills/indemnity83/logistics/ship-pr-queue"><img src="https://agentmods.dev/badge/skills/indemnity83/logistics/ship-pr-queue.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Memory Poisoning · line 226 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
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 5.1 | $0.00104 | $0.02511 |
| Opus 5 | $0.00052 | $0.01256 |
| Sonnet 5 | $0.00021 | $0.00502 |
| Haiku 4.5 | $0.00010 | $0.00251 |
Grade A, and why
ship-pr-queue 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.
How it starts
The opening of the file, as written. The whole thing — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ship the PR queue
One pass = one PR taken as far as it can go. Repeat until the queue is empty. Do not batch operations across PRs: every push re-triggers a review that costs roughly $1, so wasted pushes are wasted budget.
Build the queue
gh pr list --state open --limit 100 \
--json number,title,baseRefName,headRefName,isDraft,labels,mergeStateStatus \
--jq '.[] | select(.baseRefName|startswith("mc/"))
| select(.headRefName|startswith("release-please")|not)
| select([.labels[].name]|index("autorelease: pending")|not)
| select(.isDraft|not)
| "#\(.number)\t\(.mergeStateStatus)\t\(.baseRefName)\t\(.title)"'
Release-please PRs are excluded on both signals (head branch and label) because they are merged deliberately as part of the release cycle, not by this loop.
UNKNOWN is not a state — it means GitHub has not computed mergeability yet. Asking is
what triggers the computation, so the first query after a base moves usually returns
UNKNOWN for most of the queue. Run the query again a few seconds later and it resolves.
Never classify a PR off an UNKNOWN; you would treat a clean PR as broken and "fix" a
problem that does not exist.
Report the queue to the user before acting, then take PRs in order, CLEAN ones first —
shipping those shrinks the queue fastest and moves the base for the rest.
Classify
mergeStateStatus is the primary signal:
| Status | Meaning | Branch |
|---|---|---|
CLEAN |
green and no blockers | Ship |
BLOCKED |
a required check is pending/failing, or a review thread is unresolved | Diagnose first (below) |
DIRTY |
merge conflict with base | Fix (merge base in) |
BEHIND |
base moved | gh pr update-branch <n> |
UNSTABLE |
non-required check failing | judge: usually Fix |
BLOCKED does not imply broken. A required check that is still pending blocks the
PR exactly like a failing one, and a review takes ~2 minutes. Before changing anything,
separate the three causes:
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 · 227 lines · 104 tokens per session scan A a3b7aa2a8ac9
ship-pr-queue is a skill published in the GitHub repository Indemnity83/logistics (6 stars, last pushed 2d ago), licensed MIT. It adds 104 tokens to every session and 2,511 once invoked, about $0.0005 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 2026-09-04.
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github
GitHub via gh CLI: PRs, issues, reviews, repos, auth.
github
Full GitHub CLI control — issues, PRs, code reviews, repo management. Uses gh CLI with auth detection, rate limiting, and templates. Triggers on: github, issue, pull request, PR, code review, repo, branch, label, assignee, milestone, release, workflow, actions.
pre-publish-review
Nuclear-grade 12-agent pre-publish release gate. Runs /get-unpublished-changes to detect all changes since last npm release, spawns up to 10 ultrabrain agents for deep per-change analysis, invokes /review-work (orchestrator manual QA plus one gate reviewer) for holistic review, and 1 oracle for overall release…
parallel-pr-review
Use when asked to "review the open PRs", review a batch or stack of pull requests, or run a recurring PR-review pass on a repo — especially with many PRs, stacked branches, conflicts, or security-sensitive changes. Covers grouping, fan-out to review subagents, verdict synthesis, and posting.
no-mistakes
Validate committed feature-branch changes through the no-mistakes pipeline: intent, rebase, review, test, docs, lint, push, PR, and CI. Use when the user asks to run no-mistakes, ship safely, validate before pushing, or gate a change before it reaches upstream.