plain-portal
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.
Best use case
plain-portal is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using plain-portal should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/plain-portal/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How plain-portal Compares
| Feature / Agent | plain-portal | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Remote Portal Session Open an encrypted tunnel to a remote machine and run Python code on it. ## 1. Start the remote side and connect 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> ``` ## 2. Run commands 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>" ``` ### File transfer ``` 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. ## 3. Disconnect Kill the `connect` process to end the session. This also frees the remote process. ## Important - Sessions are **read-only** by default. Database writes will fail unless the remote was started with `--writable --yes`. - Each `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. - Use `plain portal exec` for quick queries. For heavy data export, write to `/tmp/` on the remote and `pull` the file. - If the session drops, the remote side must be restarted and a new code used to reconnect.
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