create-pr

A repository-specific workflow for creating a GitHub pull request, a proposed code change submitted for review, in TrainLCD StationAPI.

In plain words
What is it for?
Use it when opening a pull request in this repository. It can infer details from the branch and commits, but asks for confirmation when the correct choice is unclear.
Why use it?
It ensures the pull request follows the repository's template and handles its branch, assignee, change-type, issue, and test fields consistently.

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/trainlcd/stationapi/create-pr
Any agent
npx skills add TrainLCD/StationAPI --skill create-pr
Clone the repo
git clone --depth 1 https://github.com/TrainLCD/StationAPI

Made for: Claude Code, Codex.

Per session 61 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 9,210 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 $0.00061 $0.09210
Opus 5 $0.00030 $0.04605
Sonnet 5 $0.00012 $0.01842
Haiku 4.5 $0.00006 $0.00921

Measured yesterday against content hash 26dbe322d697, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

create-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 yesterday.

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.

.claude/skills/create-pr/SKILL.md · 321 lines

How it starts

The opening of the file, as written. The whole thing — 321 lines — stays where its author put it; the contents beside it link to each section on GitHub.

create-pr

このリポジトリの PR 作成手順を一本化したスキル。.github/pull_request_template.md を厳守し、Assignee・変更の種類・テスト欄を自動で組み立てる。

入力(呼び出し元が指定)

すべて任意。未指定なら下の既定値・推論で埋める。推論結果に不安があるとき(例: 多数のコミットで方向性がバラバラ)はユーザーに確認してから進める。

項目 既定値 / 推論元
base リポジトリの既定ブランチ(gh repo view --json defaultBranchRef -q .defaultBranchRef.name、StationAPI では通常 dev
head 作業コミット @ に最も近いローカルブックマーク(jj log -r 'heads(::@ & bookmarks())' --no-graph -T 'local_bookmarks.map(|b| b.name()).join("\n") ++ "\n"')。該当が無ければ手順 1 で切り出す。出力が 2 行以上のときは自動選択しない(同一コミットに複数ブックマークがある、または @ の上流に head が複数ある場合)。候補を列挙してユーザーに確認してから進める
title 下の「タイトル推論ルール」参照
summary 空なら「概要」「変更内容」本文はテンプレのコメントのみ残す
related_issue ユーザー入力を最優先。指定が #N(数値のみ)なら Closes #NCloses #N / Fixes #N / Refs #N 形式ならその接頭語を保って出力。related_issue が空のときに限り、コミット件名から Closes #N / Fixes #N / Refs #N を抽出(接頭語を維持。#N 単体表記なら Closes を補う)。両方とも見つからなければ節のコメントのみ
skip_checks false(PR本文「テスト」節のチェック欄 3 項目を ON)。true なら全 OFF。本文表示のみを制御するフラグで、Step 1 の cargo fmt / clippy / test の実際の実行は保証しない(実行可否は「コードに変更があるか」で決める)。Step 1 で cargo チェックを実行していない(=コード/データ変更なし)ケースでは、skip_checks の値に関わらず 3 項目すべて OFF にする
labels 文字列配列、または未指定。通常は未指定で OK.github/workflows/pr_labeler.yml がブランチ名と変更ファイルから自動付与する)。手動指定が必要な場合は gh pr create --label <name> で渡す(作成後に gh pr edit --add-label すると pull_request: opened トリガのワークフローに間に合わないため、必ず gh pr create 時に渡す)

タイトル推論ルール

<base>@origin..<head>@origin(jj revset)のコミット件名を対象に、以下を順に試す:

  1. コミット 1 件のみ: その件名をそのまま使う。
  2. コミット複数・共通テーマあり: 最新コミットの件名、もしくは件名群を要約した日本語の単文を使う。
  3. ブランチ名が feature/ / fix/ / data/ / chore/ / release/ で始まる: プレフィックスを取り除き、残りの kebab-case を日本語や自然文に整える。確信が持てないときは整形せずブランチ名のまま使ってよい。
  4. どれでも決まらない: 最新コミット件名を採用し、「このタイトルで作成してよいか」をユーザーに確認する。

このリポジトリの直近 PR タイトル(例: 近鉄生駒鋼索線 鳥居前駅と近鉄生駒駅をグループ接続京急本線 line_symbol2_colorのコードが違う)に倣い、簡潔な日本語の単文に整形する。Conventional Commits プレフィックス(fix: feat: など)は基本的に剥がす。整形時は意味を変えないこと。

前提条件

Read the full file on GitHub · 321 lines

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. yesterday First seen · 321 lines · 61 tokens per session scan A 26dbe322d697

Subscribe to this mod's changes

create-pr is a skill published in the GitHub repository TrainLCD/StationAPI (10 stars, last pushed 2d ago), licensed MIT. It adds 61 tokens to every session and 9,210 once invoked, about $0.0003 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 2026-08-31.

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