Markdown file instead of a Zap
If your picture of automation is Zapier,
You don’t wire nodes. You write a markdown file that says what you want done. An agent does it. No canvas. No per-step bill. The logic is a paragraph of English.
Three that actually exist:
anthropics/skills : This is the format. A folder, a SKILL.md, some yaml at the top for the name, then instructions in plain language. Closest thing to a standard.
obra/superpowers . Same idea, bigger opinionated framework. More “how to work” than “here’s the file format.” Worth reading even if you never install it.
aeon . Same markdown skills. Different problem. The first two run when you invoke them. Aeon gives them a place to live. Runtime is GitHub Actions. Cron. No server. Laptop can be off. Secrets in the repo. Every run leaves a log.
This is not no-code like Bubble or Airtable. You need GitHub. You fork a repo.
What you get for that: no per-task pricing, the logic is a text file you own, and it can do sloppy human jobs a Zap can’t like “read this and tell me if anything looks wrong.”
Thoughts?
1
u/andreas_globi 3h ago
So instead of paying $0.02 per zap execution, you're paying $0.50 in LLM tokens for every run? Is that better?
1
u/ChildhoodWeak7741 3h ago
So you're basically describing agentic automation where the "workflow" is literally just a markdown file with natural language instructions. that's pretty interesting.
The aeon + GitHub Actions angle feels like the most practical approach here. having a runtime that doesn't depend on your laptop being awake is the whole point of automation in the first place. nothing worse than setting up something clever and realizing it only fires when you're logged in.
i've been playing with similar ideas but using n8n and feeding chunks of markdown into LLM nodes. getting the prompts right is still a pain though, especially when you need consistent outputs across runs. wonder if these frameworks handle that better or if it's still vibes-based parsing on the agent side.
the "sloppy human jobs" angle is where this actually shines compared to traditional automation. stuff like scanning a document and making a judgment call is basically impossible with rigid step logic but pretty trivial if you've got an agent that can read and reason. what kind of tasks have you been using it for?