Portless Cli logo

Portless Cli

Organization
zenobi-us
portless-cli

Guides correct usage of the Portless CLI for local named URLs, monorepo workflows, HTTPS/LAN/Tailscale modes, and proxy routing pitfalls, when developers need stable local domains instead of port juggling, resulting in reproducible commands and fewer misconfiguration loops.

Overview

Publisherzenobi-us
Repositorydotfiles
Skill nameportless-cli
Stars
67
Forks
6
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by zenobi-us on GitHub. Read the source before you install it.

Installation

Install the Portless Cli AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/zenobi-us/dotfiles.git /tmp/dotfiles
mkdir -p .claude/skills
cp -r /tmp/dotfiles/files/devtools/agent/bundles/developer/skills/devtools/portless-cli .claude/skills/portless-cli
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Portless Cli in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Portless Cli on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Portless Cli is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Portless CLI

Overview

Portless maps local apps to stable named URLs like https://myapp.localhost. It removes manual port juggling and reduces cross-app cookie/origin clashes.

Source of truth: vercel-labs/portless GitHub README and portless --help.

When to Use

Use when you need:

  • Stable local hostnames instead of localhost:NNNN
  • Monorepo app naming/worktree-safe URLs
  • HTTPS local dev with trusted local CA
  • LAN or Tailscale sharing of local apps

Do not use for public production ingress.

Quick Start

bash
npm install -g portless
portless run next dev
# -> https://<project>.localhost

Explicit name:

bash
portless myapp next dev
# -> https://myapp.localhost

Core Commands

  • portless / portless run — run package dev script through proxy
  • portless run <cmd> — run command through proxy
  • portless <name> <cmd> — explicit app name
  • portless proxy start|stop
  • portless list
  • portless get <name>
  • portless trust
  • portless hosts sync|clean
  • portless service install|status|uninstall
  • portless clean

Monorepo Pattern

  • Put portless.json in repo root.
  • Optional apps map for naming overrides.
  • From monorepo root, portless starts all workspace packages with a dev script.

Example portless.json:

json
{
  "apps": {
    "apps/web": { "name": "web" },
    "apps/api": { "name": "api" }
  }
}

Critical Pitfalls

  1. Wrong syntax hallucination: No --from/--to/--path flow. Use run, <name> <cmd>, alias, get, list.
  2. Wrong package name: CLI install is portless, not vercel-labs/portless.
  3. Proxy loops between apps: If frontend proxies to another Portless host, set changeOrigin: true.
  4. Safari DNS issues: run portless hosts sync.
  5. Reserved names: run|get|alias|hosts|list|trust|clean|prune|proxy|service cannot be app names unless forced with --name.
  6. Invalid command family: MUST NOT use portless http ... (not a valid subcommand in this CLI).
  7. Invalid apps schema: In portless.json, app entries SHOULD be objects (e.g. { "name": "web" }), not ad-hoc undocumented shapes.

API Proxy Example (Vite)

ts
server: {
  proxy: {
    '/api': {
      target: 'https://api.myapp.localhost',
      changeOrigin: true,
      ws: true,
    },
  },
}

LAN / Tailscale

  • LAN mode: portless proxy start --lan
  • Tailscale share: portless myapp --tailscale next dev
  • Public Funnel: portless myapp --funnel next dev

Validation Checklist

  • portless --help shows command used exists.
  • URL resolves at https://<name>.localhost.
  • portless list shows active route.
  • Cross-app proxy does not loop (no 508 Loop Detected).
  • Output MUST NOT include portless http, --from, --to, or --path.

Frequently asked questions

What does the Portless Cli AI skill do?

Guides correct usage of the Portless CLI for local named URLs, monorepo workflows, HTTPS/LAN/Tailscale modes, and proxy routing pitfalls, when developers need stable local domains instead of port juggling, resulting in reproducible commands and fewer misconfiguration loops.

Why use Portless Cli on TypingMind?

Because you install it once and use it with any model. Portless Cli is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Portless Cli in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zenobi-us/dotfiles/tree/master/files/devtools/agent/bundles/developer/skills/devtools/portless-cli. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Portless Cli?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Portless Cli?

As many as you like. As long as a model supports skills, you can use Portless Cli with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Portless Cli AI skill free?

Yes. It is published on GitHub by zenobi-us under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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