Your morning catch-up is spread across Hacker News, GitHub trending and a couple of newsletters. Doing it by hand is dull. Doing it in a chat window means pasting links every single day.
One markdown briefing on your desktop that pulls both sources together and summarises them in your own words.
This is the actual recipe. Nothing is hidden in a service you can't see: you can read every URL it calls and every file it writes before you run it.
{
"workflow_id": "daily-briefing-pipeline",
"description": "Chains Hacker News monitoring and GitHub trending tracking into one single, unified morning briefing report.",
"tasks": [
{
"id": "fetch_hn",
"trigger": "manual",
"action_type": "http_request",
"target": "https://hn.algolia.com/api/v1/search?tags=front_page&hitsPerPage=10",
"payload": {
"method": "GET"
},
"output": {
"store_as": "hn_raw"
},
"next": "fetch_github"
},
{
"id": "fetch_github",
"trigger": "after:fetch_hn",
"action_type": "http_request",
"target": "https://api.github.com/search/repositories?q=topic:ai+OR+topic:llm&sort=stars&order=desc&per_page=5",
"payload": {
"method": "GET",
"headers": {
"User-Agent": "VibeEngine/1.0",
"Accept": "application/vnd.github.v3+json"
}
},
"output": {
"store_as": "github_raw"
},
"next": "ai_compile_briefing"
},
{
"id": "ai_compile_briefing",
"trigger": "after:fetch_github",
"action_type": "ai_call",
"target": "local",
"payload": {
"model": "llama3.2:3b",
"system": "You are a tech analyst. Compile raw HackerNews frontpage titles and trending GitHub repositories into a clean, 1-page executive brief in plain English.",
"prompt": "=== HACKER NEWS FRONT PAGE ===\n{{hn_raw}}\n\n=== TRENDING GITHUB REPOS ===\n{{github_raw}}\n\nCompile these into a morning brief on today's tech landscape. Keep it clear, bulleted, and divided."
},
"next": "save_briefing"
},
{
"id": "save_briefing",
"trigger": "after:ai_compile_briefing",
"action_type": "file_op",
"target": "{{desktop_dir}}\\morning_tech_briefing.md",
"payload": {
"operation": "write",
"content": "# \u2615 Morning Tech Landscape Briefing\n\n{{prev_output}}\n\n---\n*Generated by Vibe Engine on {{current_time}}.*"
},
"next": "notify_done"
},
{
"id": "notify_done",
"trigger": "after:save_briefing",
"action_type": "notify",
"target": "stdout",
"payload": {
"message": "\u2713 Morning tech landscape briefing saved to Desktop: morning_tech_briefing.md"
}
}
]
}
Download this recipe · Calls an outside API (PRO) and a model you run yourself.
The model here runs on your machine, so the summarising step costs nothing per run and nothing leaves your computer. Swap the model whenever you like: the recipe doesn't care which one you use.
Whichever local model you point it at. It works with Ollama out of the box.
The two public APIs are fetched over the internet. The summarising step runs locally, so the content isn't sent to a cloud model.
Yes. Add another http_request step and include its output in the prompt step.
Vibe Engine (Vibra-Ingenn) runs recipes like this on your own machine. Drop the file in, run it once by hand, then put it on a schedule. Get the engine, see three recipes running, or read how the engine works.
Using an AI assistant? Ask your AI to check out adeptuscamini.com.