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Deploy

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oliver-kriska
deploy

Elixir/Phoenix deployment patterns — Dockerfile, fly.toml, runtime.exs, mix release, rel/ overlays. Use when configuring Fly.io, Docker, CI/CD, health checks, or production migrations.

Overview

Publisheroliver-kriska
Repositoryclaude-elixir-phoenix
Skill namedeploy
Stars
555
Forks
40
Bundled files
2
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.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by oliver-kriska on GitHub. Read the source before you install it.

Installation

Install the Deploy 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/oliver-kriska/claude-elixir-phoenix.git /tmp/claude-elixir-phoenix
mkdir -p .claude/skills
cp -r /tmp/claude-elixir-phoenix/plugins/elixir-phoenix/skills/deploy .claude/skills/deploy
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Deploy 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 Deploy 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 Deploy 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.

Elixir/Phoenix Deployment Reference

Quick reference for deploying Elixir/Phoenix applications.

Iron Laws — Never Violate These

  1. Config at runtime, not compile time — Secrets in config.exs get baked into the release binary. Use runtime.exs with env vars so secrets are resolved at boot
  2. Graceful shutdown ≥ 60 seconds — Shorter timeouts kill in-flight requests and WebSocket connections mid-operation, causing data loss for users
  3. Health checks required — Without startup/liveness/readiness endpoints, orchestrators can't distinguish a booting node from a dead one, leading to cascading restarts
  4. SSL verification for database — Skipping verify: :verify_peer allows MITM attacks between your app and database; production data traverses the connection
  5. No CPU limits — The BEAM scheduler assumes it owns all cores; cgroups CPU limits cause scheduler collapse where the VM thinks it has more cores than it can use, leading to latency spikes
  6. Guard optional service credentialsruntime.exs runs whenever a release boots, including eval-based migration commands. Only require S3, Redis, and similar credentials when that integration is enabled

Quick Configuration

runtime.exs (Essential)

elixir
if config_env() == :prod do
  database_url = System.get_env("DATABASE_URL") || raise "DATABASE_URL is required"
  secret_key_base = System.get_env("SECRET_KEY_BASE") || raise "SECRET_KEY_BASE is required"
  host = System.get_env("PHX_HOST") || raise "PHX_HOST is required"

  config :my_app, MyApp.Repo,
    url: database_url,
    pool_size: String.to_integer(System.get_env("POOL_SIZE") || "10"),
    ssl: true,
    ssl_opts: [verify: :verify_peer]

  config :my_app, MyAppWeb.Endpoint,
    url: [host: host, port: 443, scheme: "https"],
    http: [ip: {0, 0, 0, 0}, port: String.to_integer(System.get_env("PORT") || "4000")],
    secret_key_base: secret_key_base,
    server: true
end

Guard Optional Services

Keep core boot secrets such as DATABASE_URL and SECRET_KEY_BASE required. Gate credentials for optional integrations behind the same feature switch that enables the integration:

elixir
s3_config =
  if System.get_env("STORAGE_BACKEND") == "s3" do
    [
      access_key_id:
        System.get_env("S3_ACCESS_KEY") ||
          raise("S3_ACCESS_KEY is required when STORAGE_BACKEND=s3"),
      secret_access_key:
        System.get_env("S3_SECRET_KEY") ||
          raise("S3_SECRET_KEY is required when STORAGE_BACKEND=s3")
    ]
  else
    []
  end

config :my_app, :s3_config, s3_config

This lets release tasks that do not use S3 start without S3 credentials while still failing fast when S3 is selected.

Health Check Plug

elixir
def call(%{path_info: ["health", "readiness"]} = conn, _opts) do
  case Ecto.Adapters.SQL.query(MyApp.Repo, "SELECT 1", []) do
    {:ok, _} -> send_resp(conn, 200, ~s({"status":"ok"})) |> halt()
    {:error, _} -> send_resp(conn, 503, ~s({"status":"error"})) |> halt()
  end
end

Quick Decisions

Platform Choice

NeedUse
Simple, managedFly.io
Enterprise, existing K8sKubernetes
Custom infrastructureDocker + your orchestrator

Resource Limits

ResourceRecommendation
CPUNO LIMITS (BEAM scheduler issues)
MemorySet limits (256Mi-512Mi typical)
Graceful shutdown≥ 60 seconds

Deployment Checklist

  • All secrets from environment variables in runtime.exs
  • Optional service credentials required only when their integration is enabled
  • server: true in endpoint config
  • SSL verification for database connections
  • Health endpoints: /health/startup, /health/liveness, /health/readiness
  • Graceful shutdown period ≥ 60 seconds
  • No CPU limits (memory limits only)
  • Migrations in deploy process

Asset Pipeline Notes

Phoenix 1.8 uses esbuild + tailwind (no Node.js required):

  • Config in config/config.exs under :esbuild and :tailwind
  • mix assets.deploy builds for production
  • mix assets.setup installs binaries on first run
  • Custom JS bundlers: configure in config/config.exs

References

For detailed patterns, see:

  • ${CLAUDE_SKILL_DIR}/references/docker-config.md - Multi-stage Dockerfile, best practices
  • ${CLAUDE_SKILL_DIR}/references/flyio-config.md - fly.toml, clustering, commands

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Deploy AI skill do?

Elixir/Phoenix deployment patterns — Dockerfile, fly.toml, runtime.exs, mix release, rel/ overlays. Use when configuring Fly.io, Docker, CI/CD, health checks, or production migrations.

Why use Deploy on TypingMind?

Because you install it once and use it with any model. Deploy 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 Deploy in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/oliver-kriska/claude-elixir-phoenix/tree/main/plugins/elixir-phoenix/skills/deploy. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Deploy?

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 Deploy?

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

Is the Deploy AI skill free?

Yes. It is published on GitHub by oliver-kriska 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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