.claude/skills/plain-portal/SKILL.md
Open a remote Python shell on a production machine via encrypted tunnel. Use when you need to inspect production data, debug issues, run queries, or transfer files.
npx skillsauth add dropseed/plain plain-portalInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Open an encrypted tunnel to a remote machine and run Python code on it.
The remote side must be running first. Either start it yourself (if you have access to the platform CLI) or ask the user to start it:
| Platform | Command |
| ---------- | --------------------------------------------------- |
| Heroku | heroku run plain portal start |
| Fly.io | fly ssh console -C "plain portal start" |
| Kubernetes | kubectl exec -it deploy/app -- plain portal start |
| Docker | docker exec -it container plain portal start |
| SSH | ssh server plain portal start |
Both start and connect are long-running foreground processes. If you run start yourself, use run_in_background so you don't block. Once it prints a portal code (e.g. 7-crossword-pineapple), read the code from the output. If the user ran it, ask them for the code.
Then connect (also use run_in_background):
uv run plain portal connect <code>
Execute Python code on the remote machine:
uv run plain portal exec "<code>"
Output streams line by line in real time. The last expression's value is returned (like a REPL).
For long-running commands, increase the timeout (default 120s):
uv run plain portal exec --timeout 300 "<code>"
For machine-readable output:
uv run plain portal exec --json "<expression>"
uv run plain portal pull <remote_path> <local_path>
uv run plain portal push <local_path> <remote_path>
Push is restricted to /tmp/ on the remote machine.
Kill the connect process to end the session. This also frees the remote process.
--writable --yes.exec gets a fresh namespace. Variables don't carry between commands. Put setup and queries in one code block if they depend on each other.plain portal exec for quick queries. For heavy data export, write to /tmp/ on the remote and pull the file.documentation
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data-ai
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