/api/v1/recommendObtén recomendaciones de kits para una plataforma de IA + caso de uso.
Cuerpo del request
{
"ai_platform": "claude", // or chatgpt | codex | gemini | cursor | any
"use_case": "shipping a SaaS on Next.js",
"max_results": 3 // optional, default 3, max 10
}Ejemplo
curl
curl https://lumenari.io/api/v1/recommend \
-H "Authorization: Bearer lmn_..." \
-H "Content-Type: application/json" \
-d '{"ai_platform":"claude","use_case":"shipping a SaaS","max_results":3}'javascript
const r = await fetch("https://lumenari.io/api/v1/recommend", {
method: "POST",
headers: {
"Authorization": "Bearer lmn_...",
"Content-Type": "application/json",
},
body: JSON.stringify({
ai_platform: "claude",
use_case: "shipping a SaaS",
max_results: 3,
}),
}).then(r => r.json());python
r = requests.post(
"https://lumenari.io/api/v1/recommend",
headers={"Authorization": "Bearer lmn_..."},
json={
"ai_platform": "claude",
"use_case": "shipping a SaaS",
"max_results": 3,
},
).json()Respuesta
{
"recommendations": [
{
"kit_id": "ts-next-production",
"kit_slug": "ts-next-production",
"kit_name": "TypeScript + Next.js Production Pack",
"score": 1.0,
"reasoning": "Your stack matches this kit directly — App Router patterns and Supabase wiring."
}
],
"fallback": false
}