ship-gate
Pre-production audit that scans a codebase for security, database, deployment, code quality, AI/LLM, dependency, frontend, and observability issues. Intercepts deploy commands and blocks until critical items pass. Stack-agnostic. Use for "run ship gate", "am I ready to ship", "pre-launch audit", "can I deploy", "push to production", "go live checklist", "preflight check". Not for CI/CD setup or infra provisioning.
下記のコマンドをコピーしてターミナル(Mac/Linux)または PowerShell(Windows)に貼り付けてください。 ダウンロード → 解凍 → 配置まで全自動。
mkdir -p ~/.claude/skills && cd ~/.claude/skills && curl -L -o ship-gate.zip https://jpskill.com/download/21873.zip && unzip -o ship-gate.zip && rm ship-gate.zip
$d = "$env:USERPROFILE\.claude\skills"; ni -Force -ItemType Directory $d | Out-Null; iwr https://jpskill.com/download/21873.zip -OutFile "$d\ship-gate.zip"; Expand-Archive "$d\ship-gate.zip" -DestinationPath $d -Force; ri "$d\ship-gate.zip"
完了後、Claude Code を再起動 → 普通に「動画プロンプト作って」のように話しかけるだけで自動発動します。
💾 手動でダウンロードしたい(コマンドが難しい人向け)
- 1. 下の青いボタンを押して
ship-gate.zipをダウンロード - 2. ZIPファイルをダブルクリックで解凍 →
ship-gateフォルダができる - 3. そのフォルダを
C:\Users\あなたの名前\.claude\skills\(Win)または~/.claude/skills/(Mac)へ移動 - 4. Claude Code を再起動
⚠️ ダウンロード・利用は自己責任でお願いします。当サイトは内容・動作・安全性について責任を負いません。
🎯 このSkillでできること
下記の説明文を読むと、このSkillがあなたに何をしてくれるかが分かります。Claudeにこの分野の依頼をすると、自動で発動します。
📦 インストール方法 (3ステップ)
- 1. 上の「ダウンロード」ボタンを押して .skill ファイルを取得
- 2. ファイル名の拡張子を .skill から .zip に変えて展開(macは自動展開可)
- 3. 展開してできたフォルダを、ホームフォルダの
.claude/skills/に置く- · macOS / Linux:
~/.claude/skills/ - · Windows:
%USERPROFILE%\.claude\skills\
- · macOS / Linux:
Claude Code を再起動すれば完了。「このSkillを使って…」と話しかけなくても、関連する依頼で自動的に呼び出されます。
詳しい使い方ガイドを見る →- 最終更新
- 2026-05-18
- 取得日時
- 2026-05-18
- 同梱ファイル
- 4
📖 Claude が読む原文 SKILL.md(中身を展開)
この本文は AI(Claude)が読むための原文(英語または中国語)です。日本語訳は順次追加中。
Ship Gate
Pre-production audit that scans a codebase and reports pass/fail/manual across 8 categories before anything ships.
Intercept Behavior
When the user says "push to production", "deploy", "ship it", "go live", or similar deploy-intent phrases, do NOT proceed with deployment. Instead:
- Ask: "Have you run the ship gate? Want me to scan now?"
- If yes, run the full audit below.
- If the user says they already ran it, ask when. If more than 24 hours ago or if code changed since, recommend re-running.
How It Works
Step 1: Detect Stack
Run these checks in order to identify the project stack:
Framework detection:
package.json exists -> Node.js project
"next" in dependencies -> Next.js
"react" in dependencies -> React (if not Next.js)
"vue" in dependencies -> Vue
"svelte" in dependencies -> Svelte
"astro" in dependencies -> Astro
"express" in dependencies -> Express
"fastify" in dependencies -> Fastify
"hono" in dependencies -> Hono
requirements.txt or pyproject.toml -> Python project
"django" present -> Django
"flask" present -> Flask
"fastapi" present -> FastAPI
go.mod exists -> Go project
Cargo.toml exists -> Rust project
Database detection:
"@supabase/supabase-js" in package.json -> Supabase
supabase/ directory exists -> Supabase
"prisma" in dependencies -> Prisma (check schema for DB type)
"mongoose" in dependencies -> MongoDB
"pg" or "postgres" in dependencies -> PostgreSQL
firebase.json or .firebaserc exists -> Firebase
Deploy target detection:
vercel.json or .vercel/ exists -> Vercel
netlify.toml exists -> Netlify
Dockerfile exists -> Docker/VPS
fly.toml exists -> Fly.io
railway.json exists -> Railway
.platform/applications.yaml -> Platform.sh
Auth detection:
"@clerk" in dependencies -> Clerk
"next-auth" in dependencies -> NextAuth
"@supabase/auth-helpers" in deps -> Supabase Auth
"firebase/auth" in imports -> Firebase Auth
AI/LLM detection:
"openai" in dependencies -> OpenAI
"@anthropic-ai/sdk" in dependencies -> Claude API
"@google/generative-ai" in deps -> Gemini
Report detected stack before proceeding. This determines which checks
are relevant. Checks tagged with a specific stack in references/checks.md
are skipped if that stack is not detected.
Step 2: Run Automated Checks
Run categories in this order: SEC, DB, CODE, DEP, AI, DEPLOY, FE, OBS. Security and database first because they produce the most critical findings.
For each category, run every auto-scannable check from
references/checks.md using the patterns in references/patterns.md.
Report progress after each category completes:
[1/8] Security: 3 FAIL, 12 PASS, 3 SKIP
[2/8] Database: 1 FAIL, 5 PASS, 6 SKIP
...
Report results as:
- PASS: check passed
- FAIL: issue found (with file path and line number)
- SKIP: not applicable to this stack
Step 3: Manual Confirmation
For checks that cannot be automated (backup restore tested, rollback plan exists, staging test passed), present them as a checklist and ask the user to confirm each one.
Step 4: Verdict
Classify results into three severities:
- CRITICAL: must fix before shipping (secrets exposed, no auth on routes, no HTTPS, SQL injection vectors, no RLS on Supabase tables)
- HIGH: should fix before shipping (no error boundaries, no rate limiting, console.logs in production, no pagination)
- ADVISORY: recommended but not blocking (no OG tags, no custom 404, no analytics, no SBOM)
Final output:
SHIP GATE REPORT
================
Stack: Next.js + Supabase + Vercel
Scan time: 12s
CRITICAL (3 items, must fix)
FAIL [SEC-01] API key found in src/lib/api.ts:14
FAIL [DB-07] RLS not enabled on "profiles" table
FAIL [SEC-05] No CSRF protection on /api/checkout
HIGH (5 items, should fix)
FAIL [CODE-01] 12 console.log statements in production code
FAIL [CODE-03] Empty catch block in src/utils/auth.ts:45
FAIL [DEP-04] 3 critical npm audit vulnerabilities
FAIL [DEPLOY-05] No rollback plan documented
MANUAL [DEPLOY-06] Staging test not confirmed
ADVISORY (4 items, recommended)
FAIL [FE-01] Missing OG meta tags
FAIL [FE-03] No custom 404 page
PASS [OBS-01] Error monitoring configured
SKIP [AI-01] No AI/LLM usage detected
VERDICT: DO NOT SHIP (3 critical issues)
Fix critical items and re-run.
If zero critical items remain, verdict is: CLEAR TO SHIP. If only high items remain, verdict is: SHIP WITH CAUTION (acknowledge risks).
Categories
Eight categories, each with a code prefix. Full check details in
references/checks.md.
| Prefix | Category | Auto | Manual | Tool |
|---|---|---|---|---|
| SEC | Security | 15 | 3 | 0 |
| DB | Database | 7 | 5 | 0 |
| DEPLOY | Deployment | 3 | 8 | 0 |
| CODE | Code Quality | 11 | 0 | 1 |
| AI | AI/LLM Security | 5 | 3 | 0 |
| DEP | Dependencies | 5 | 0 | 1 |
| FE | Frontend Quality | 7 | 3 | 0 |
| OBS | Observability | 2 | 5 | 0 |
Scope
This skill audits. It does not fix. When it finds issues, it reports them with file locations and remediation guidance. The user or another skill (systematic-debugging, backend-patterns, shadcn-stack) handles the fix.
This skill does not:
- Set up CI/CD pipelines
- Provision infrastructure
- Configure monitoring tools
- Run after deployment (it is pre-deploy only)
Integration Points
- karpathy-coder: run ship-gate after karpathy-check passes — simplicity first, then production readiness
- adversarial-reviewer: deep security review for items ship-gate flags as critical
- security-pen-testing: penetration testing methodology for SEC-category findings
- code-reviewer: general code quality review complements ship-gate's automated checks
同梱ファイル
※ ZIPに含まれるファイル一覧。`SKILL.md` 本体に加え、参考資料・サンプル・スクリプトが入っている場合があります。
- 📄 SKILL.md (6,606 bytes)
- 📎 references/checks.md (19,088 bytes)
- 📎 references/patterns.md (16,780 bytes)
- 📎 scripts/ship_gate_scanner.py (50,439 bytes)