Borrowing it
Nothing to install: this file belongs to guillermoscript/lms-front. 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/guillermoscript/lms-front/master/.agents/skills/ship-pr/SKILL.mdgit clone --depth 1 https://github.com/guillermoscript/lms-frontWrote 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/guillermoscript/lms-front/ship-pr)<a href="https://agentmods.dev/skills/guillermoscript/lms-front/ship-pr"><img src="https://agentmods.dev/badge/skills/guillermoscript/lms-front/ship-pr/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/guillermoscript/lms-front/ship-pr"><img src="https://agentmods.dev/badge/skills/guillermoscript/lms-front/ship-pr.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00144 | $0.02477 |
| Opus 5.5 | $0.00058 | $0.00991 |
| Sonnet 5.5 | $0.00029 | $0.00495 |
| Haiku 4.5 | $0.00014 | $0.00248 |
Grade A, and why
ship-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 1mo 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 — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ship PR — from pushed branch to announced, reviewable PR
The PR body is the QA script and the announcement is what actually gets the work reviewed — write both for the teammates who consume them, not for the user in this chat. Everything GitHub or Slack sees is a permanent record: normal, professional, full-sentence English.
Config (PR template path, Slack channel, default reviewer) comes from
.claude/gh-workflow.config.json — resolve missing pieces via the
gh-repo-config skill. Board operations go through the gh-board
skill. Neither being configured blocks a PR; unconfigured features are
skipped and noted.
Division of labor
The main agent does exactly two kinds of work here: author content (the PR title + body, the Slack message — these need session context and judgment) and decide metadata (labels, milestone, size — deciding takes judgment, applying doesn't). Every mechanical action — creating the PR, applying labels/milestone/assignee, board moves, the Slack post — goes to a subagent that receives the authored content plus exact commands and returns only what's needed next (PR URL, board item id).
Two rules keep that delegation honest — a subagent that can't find an authored file will fabricate a fluent replacement, and every signal except the content itself will report success:
- Mark every noun in the prompt. Each file or text is given or
to-produce. For every given file: "This file already exists and is
final — do NOT create, edit, or overwrite it; only pass its path to the
command." Authored text travels with "post this EXACTLY, verbatim". Name
authored files uniquely (
pr-<N>-body.md, notbody.md) so a stray write is detectable. - Verify content, not exit codes. After the subagent runs, fetch what
was actually published (
gh pr view <PR> --json title,body, the posted comment viagh api .../comments/<id> -q .body, the Slack message) and compare it to what you authored. If it drifted, edit in place —gh pr edit/gh api -X PATCHkeeps thread position, unlike delete-and-repost — using corrected content written to a fresh, uniquely-named file, not the possibly-clobbered original.
What ships with it
1 file 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.
- 1mo ago First seen · 197 lines · 144 tokens per session scan A a05df1201be6
ship-pr is a skill published in the GitHub repository guillermoscript/lms-front (40 stars, last pushed today), licensed MIT. It adds 144 tokens to every session and 2,477 once invoked, about $0.0006 per session on Opus 5.5. 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.
Other skills, from other repositories
understand-pr
Review a PR the way a seasoned maintainer would — build an independent model before seeing the diff, investigate the implementation and history, verify material claims, and return a concise briefing. Use for any PR review, self-review, or re-review.
factory-gitlab-review
Review a GitLab merge request for a Factory work item using brokered source-control tools.
factory-gitlab-rereview
Re-review a GitLab merge request after new commits and reconcile the previous review.
tuturuuu-review-comments
Inspect, fix, and resolve Tuturuuu pull-request review threads.
review-animations
Reviews animation and motion code against a high craft bar derived from Emil Kowalski's design engineering philosophy. Default to flagging; approval is earned.
ship-feature
End-to-end feature delivery — implement a feature, verify builds/tests pass, open a fully-filled draft PR, then automatically push every feedback round and review iteration to the same PR. Use when the user asks to implement or build a feature, fix-and-ship a change, or iterate on an existing feature PR.