tailscale

el-feo/ai-context · updated Apr 8, 2026

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$npx skills add https://github.com/el-feo/ai-context --skill tailscale
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summary

Use tailscale set to change settings without reconnecting. Use tailscale up for initial setup.

skill.md

Tailscale Network Management

Quick Start

# Install (Linux)
curl -fsSL https://tailscale.com/install.sh | sh

# Install (macOS)
brew install tailscale

# Connect and authenticate
sudo tailscale up

# Check status
tailscale status

# Get your Tailscale IP
tailscale ip -4

Common Operations

Connection Management

tailscale up                    # Connect
tailscale down                  # Disconnect (daemon stays running)
tailscale status                # View peers
tailscale status --json | jq    # Detailed network map
tailscale ping machine-name     # Test connectivity (ignores ACLs)
tailscale ping --icmp machine-name  # Test with ACLs
tailscale set --exit-node=name  # Use exit node
tailscale set --exit-node=      # Stop using exit node

Use tailscale set to change settings without reconnecting. Use tailscale up for initial setup.

Subnet Router Setup

Run scripts/setup_subnet_router.sh <subnet_cidr> [auth_key] for automated setup.

Manual steps:

  1. Enable IP forwarding on the router device
  2. sudo tailscale up --advertise-routes=192.168.1.0/24
  3. Approve routes in admin console (Machines > device > Edit route settings)
  4. Linux clients: sudo tailscale up --accept-routes

Exit Node Setup

Run scripts/setup_exit_node.sh [auth_key] for automated setup.

Manual steps:

  1. Enable IP forwarding on the exit node
  2. sudo tailscale up --advertise-exit-node
  3. Approve in admin console (Machines > device > Edit route settings > Use as exit node)
  4. Clients: tailscale set --exit-node=node-name --exit-node-allow-lan-access

Tailscale SSH

# Enable on server
sudo tailscale set --ssh

# Connect from client (no special setup needed)
ssh machine-name

Requires both network access grant and SSH ACL rule. See acl-examples.md for SSH ACL patterns.

Serve and Funnel

# Serve locally to tailnet
tailscale serve 3000

# Expose to public internet (ports 443, 8443, or 10000 only)
tailscale funnel 3000

# TCP forwarding with TLS termination
tailscale serve --tls-terminated-tcp=5432 localhost:5432

# Check status / turn off
tailscale serve status
tailscale serve off

Access Control

Use Grants (modern, recommended) over ACLs (legacy). Both work, but Grants support application-layer capabilities.

{
  "groups": {
    "group:engineering": ["[email protected]"]
  },
  "tagOwners": {
    "tag:server": ["group:engineering"]
  },
  "grants": [
    {
      "src": ["group:engineering"],
      "dst": ["tag:server"],
      "ip": ["22", "443"]
    }
  ]
}

Key patterns: Use groups for people, tags for machines. Always include both network grants and SSH rules for SSH access.

For detailed ACL scenarios, SSH access patterns, posture checks, auto-approvers, GitOps integration, and common mistakes, see acl-examples.md.

Reference Files

  • cli-reference.md - Complete CLI command reference with all flags, target formats, and platform-specific notes
  • acl-examples.md - Detailed ACL/grants configuration: team-based access, dev/staging/prod isolation, SSH patterns, posture checks, auto-approvers, GitOps, migration from ACLs to Grants
  • api-usage.md - REST API, Terraform provider, Python SDK, webhooks, automation examples
  • troubleshooting.md - Connectivity diagnostics, subnet router issues, exit node issues, SSH problems, MagicDNS, performance tuning, common error messages
  • production-setup.md - Architecture patterns, HA setup, security hardening, IaC (Terraform/Ansible/K8s), monitoring, DR, operational procedures

Scripts

  • scripts/setup_subnet_router.sh <subnet_cidr> [auth_key] - Automated subnet router setup (installs Tailscale, enables IP forwarding, configures routes)
  • scripts/setup_exit_node.sh [auth_key] - Automated exit node setup (installs Tailscale, enables IP forwarding, advertises as exit node)
how to use tailscale

How to use tailscale on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add tailscale
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/el-feo/ai-context --skill tailscale

The skills CLI fetches tailscale from GitHub repository el-feo/ai-context and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/tailscale

Reload or restart Cursor to activate tailscale. Access the skill through slash commands (e.g., /tailscale) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.843 reviews
  • Ira Diallo· Dec 28, 2024

    Keeps context tight: tailscale is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Ishan Harris· Dec 24, 2024

    tailscale reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Ishan Ndlovu· Dec 8, 2024

    We added tailscale from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Layla Dixit· Dec 8, 2024

    Solid pick for teams standardizing on skills: tailscale is focused, and the summary matches what you get after install.

  • Ira Abebe· Nov 27, 2024

    tailscale has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Ishan Huang· Nov 19, 2024

    Registry listing for tailscale matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Amina Mensah· Oct 18, 2024

    tailscale fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Layla Smith· Oct 10, 2024

    Useful defaults in tailscale — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Oshnikdeep· Sep 25, 2024

    Useful defaults in tailscale — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Isabella Kapoor· Sep 25, 2024

    Keeps context tight: tailscale is the kind of skill you can hand to a new teammate without a long onboarding doc.

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