Deploy Kit

Simplifie le déploiement d'apps web sur Vercel, Railway et Supabase en détectant le projet, vérifiant les CLI, recommandant la plateforme et exécutant le dép...

Security Scan

The skill's code and instructions are consistent with a CLI-based deployment helper for Vercel, Railway and Supabase; nothing in the package requests unrelated credentials or hidden network endpoints.

Purpose & Capability

Name/behavior align: the SKILL.md and scripts/deploy.py focus on detecting project type, checking CLI availability, recommending a platform, and running platform CLIs to deploy. No unrelated credentials, binaries, or system paths are requested.

Instruction Scope

SKILL.md instructs the agent to detect projects, verify CLIs, and always ask for confirmation before deploying. The script runs subprocesses to invoke platform CLIs (vercel, railway, supabase) which is expected for a deploy helper — but those CLIs (and the project's build steps they trigger) can execute arbitrary code from the repository during build/runtime, so the agent/user should be aware and confirm deployments before running in sensitive environments.

Install Mechanism

There is no install spec in the skill (instruction-only + a helper script) which is low risk. The bundled reference docs include example install commands (npm global installs and a curl | sh line for Railway in the reference) — these are not executed by the skill but are potentially risky if blindly run by a user.

Credentials

The skill does not request environment variables or credentials. References mention CLI authentication (interactive login or tokens) which is appropriate for deployment CLIs; nothing indicates unnecessary access to unrelated secrets or system config.

Persistence & Privilege

always is false and the skill does not request persistent elevated privileges or attempt to modify other skills or system-wide settings. Model invocation is allowed (default) which is normal for a user-invocable skill.

Assessment

This skill appears to do what it says: detect projects and run Vercel/Railway/Supabase CLIs to deploy. Before using it, verify you trust the project being deployed (build steps can run arbitrary code), confirm the skill asks you before executing deploy commands (it does), and avoid pasting secret tokens into chat. If you follow reference install commands, prefer package manager installs (brew/npm) from official sources and be cautious about running curl | sh. Run deployments first in a staging environment and inspect the repository and any referenced scripts before deploying to production.

Deploy Kit — Skill de Déploiement Web

Simplifie le déploiement d'apps web sur Vercel, Railway et Supabase via leurs CLIs.

Quand utiliser ce skill

L'utilisateur demande de déployer une app, créer une base de données, configurer un hébergement, ou gérer des variables d'environnement sur ces plateformes.

Workflow principal

1. Détecter le projet

python3 skills/deploy-kit/scripts/deploy.py detect <chemin>

Retourne : framework, langage, fichiers clés trouvés.

2. Vérifier les CLIs disponibles

python3 skills/deploy-kit/scripts/deploy.py check

Si un CLI manque, guide l'installation (voir références).

3. Recommander une plateforme

python3 skills/deploy-kit/scripts/deploy.py recommend <chemin>

Type de projet	Plateforme recommandée
Frontend statique / SSR (Next, Astro, Vite, Svelte, Nuxt)	Vercel
Backend / API (Express, Flask, FastAPI, Django)	Railway
App full-stack avec BDD	Railway + Supabase
BDD / Auth / Storage / Edge Functions	Supabase

4. Déployer

python3 skills/deploy-kit/scripts/deploy.py deploy <chemin> --platform <vercel|railway|supabase>

⚠️ TOUJOURS demander confirmation avant de déployer. Le script demande aussi une confirmation interactive.

Détection de projet — Règles

Fichier trouvé	Framework détecté
next.config.*	Next.js
astro.config.*	Astro
vite.config.*	Vite
svelte.config.*	SvelteKit
nuxt.config.*	Nuxt
remix.config.* / app/root.tsx	Remix
angular.json	Angular
requirements.txt / Pipfile	Python
manage.py	Django
package.json → scripts.start	Node.js app
Dockerfile	Docker (Railway)
supabase/config.toml	Supabase project

Variables d'environnement

• Vercel : vercel env add NOM_VAR ou via dashboard
• Railway : railway variables set NOM=VALEUR
• Supabase : secrets via supabase secrets set NOM=VALEUR

Toujours vérifier .env / .env.local pour les vars existantes avant déploiement.

Domaines custom

• Vercel : vercel domains add mondomaine.com
• Railway : railway domain (génère un sous-domaine), custom via dashboard

Références détaillées

Charger à la demande selon la plateforme :

• skills/deploy-kit/references/vercel.md — Vercel CLI complet
• skills/deploy-kit/references/railway.md — Railway CLI complet
• skills/deploy-kit/references/supabase.md — Supabase CLI complet

Commandes rapides

Action	Commande
Deploy preview Vercel	vercel
Deploy prod Vercel	vercel --prod
Deploy Railway	railway up
Push DB Supabase	supabase db push
Deploy edge function	supabase functions deploy <nom>
Voir les logs	vercel logs <url> / railway logs
Lister les projets	vercel ls / railway list

Règles pour l'agent

1. Ne jamais déployer sans confirmation explicite de l'utilisateur
2. Toujours détecter le projet avant de recommander
3. Vérifier que le CLI est installé et authentifié
4. Charger la référence détaillée de la plateforme si besoin de commandes avancées
5. Proposer un déploiement preview avant production
6. Mentionner les coûts potentiels si projet hors free tier