AutoDiscovery is an AI-driven scientific discovery platform that runs iterative experiments guided by Bayesian surprise and MCTS optimization.
This skill is a router. Inspect the user's request, pick one workflow, then read its .md file in workflows/ and follow it. Do not execute a workflow from memory — always open the file first.
Workflows
| Name | Purpose | Detailed instructions |
|---|---|---|
| remote | Use the hosted AutoDiscovery service via asta autodiscovery. Requires Asta auth and consumes credits; runs execute on Asta infrastructure. |
workflows/remote.md |
| local | Run AutoDiscovery locally via the asta-autodiscovery CLI. Executes on the user's machine with user-provided API keys for making LLM calls |
workflows/local.md |
Routing
1. Honor explicit requests
- "local", "on my machine", "offline", "run it myself", or any reference to the
asta-autodiscoveryCLI → local. - "remote", "hosted", "cloud", "Asta service", "my runs", "credits", or any reference to the
asta autodiscovery(note the space) subcommand → remote.
2. Use signals when the request is ambiguous
- Past runs are stored in a local directory for local runs, or on the remote server for remote runs
- If the user is starting fresh and has not indicated a preference, ask which workflow they want before proceeding. Mention the tradeoff: remote uses Asta credentials and rate limits; local runs with the user's hardware and credentials.
3. No chaining
The two workflows are independent. Do not silently switch between them mid-task.