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Phoenix Ops

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bobmatnyc
phoenix-ops

Phoenix operations and deployment: releases, runtime configuration, clustering, libcluster, telemetry/logging, secrets, assets, background jobs, and production hardening on the BEAM.

Overview

Publisherbobmatnyc
Repositoryclaude-mpm-skills
Skill namephoenix-ops
Stars
75
Forks
19
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

    Published by bobmatnyc on GitHub. Read the source before you install it.

Installation

Install the Phoenix Ops 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/bobmatnyc/claude-mpm-skills.git /tmp/claude-mpm-skills
mkdir -p .claude/skills
cp -r /tmp/claude-mpm-skills/toolchains/elixir/ops/phoenix-ops .claude/skills/phoenix-ops
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Phoenix Ops 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 Phoenix Ops 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 Phoenix Ops 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.

Phoenix Operations and Deployment (Elixir/BEAM)

Production-ready Phoenix apps rely on releases, runtime configuration, telemetry, clustering, and secure endpoints. The BEAM enables rolling restarts and supervision resilience when configured correctly.

Releases and Runtime Config

bash
MIX_ENV=prod PHX_SERVER=true mix assets.deploy
MIX_ENV=prod mix release
_build/prod/rel/my_app/bin/my_app eval "IO.puts(:os.type())"
_build/prod/rel/my_app/bin/my_app start

config/runtime.exs for env-driven settings:

elixir
config :my_app, MyApp.Repo,
  url: System.fetch_env!("DATABASE_URL"),
  pool_size: String.to_integer(System.get_env("POOL_SIZE", "10")),
  ssl: true

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

Secrets

  • Prefer env vars or secret stores (AWS/GCP KMS, Vault); avoid embedding in configs.
  • Generate SECRET_KEY_BASE with mix phx.gen.secret.

Clustering and PubSub/Presence

Add libcluster for automatic node discovery:

elixir
# mix.exs deps
{:libcluster, "~> 3.3"},
{:phoenix_pubsub, "~> 2.1"},

# application.ex
topologies = [
  dns_poll: [
    strategy: Cluster.Strategy.DNSPoll,
    config: [poll_interval: 5_000, query: "my-app.internal"],
    connect: {:net_adm, :ping}
  ]
]

children = [
  {Cluster.Supervisor, [topologies, [name: MyApp.ClusterSupervisor]]},
  {Phoenix.PubSub, name: MyApp.PubSub},
  MyAppWeb.Endpoint
]

Guidelines

  • Share secret_key_base across nodes for consistent session signing.
  • Use distributed PubSub for Presence; ensure node connectivity before enabling Presence-heavy features.
  • For blue/green, keep cookies compatible between versions.

Telemetry, Logging, and Metrics

  • Install opentelemetry_phoenix and opentelemetry_ecto for traces/metrics.
  • Add Plug.Telemetry and LoggerJSON or structured logging.
  • Export metrics (Prometheus/OpenTelemetry) via :telemetry_poller for VM stats (reductions, memory, schedulers).
  • Set LOGGER_LEVEL=info in prod; use :debug only for troubleshooting.

HTTP and Network Hardening

  • Enforce HTTPS (force_ssl), HSTS, secure cookies (same_site, secure), and proper content_security_policy.
  • CORS: configure cors_plug for API origins.
  • Rate limiting: apply plugs (ETS/Cachex token bucket) or edge (NGINX/Cloudflare).
  • Uploads: prefer presigned URLs; limit request body size (:max_request_line_length, :max_header_value_length).

Assets and Static Delivery

  • mix assets.deploy runs npm/tailwind/esbuild and digests assets.
  • Serve static files via CDN/reverse proxy; ensure cache-control headers set in Endpoint.
  • Disable unused watchers in production to trim image size.

Background Jobs

  • Oban recommended for retries/backoff, scheduled jobs, and isolation; supervise in application.ex.
  • Configure queues via runtime env; monitor with Oban Web/Pro or telemetry.
  • For CPU-heavy tasks, consider pooling or external workers to avoid blocking schedulers.

Deployment Patterns

  • Containers: multi-stage builds; run mix deps.get --only prod, mix compile, mix assets.deploy, then mix release.
  • Systemd: run release binary as service with Environment= secrets; add Restart=on-failure.
  • Fly/Gigalixir/Render: supply env vars, attach Postgres/Redis, open long-lived WebSocket ports.
  • Blue/green or canary: keep DB migrations compatible; deploy code first, then run migrations; keep feature flags for schema changes.

Observability and Health

  • Add /health and /ready endpoints (Repo check + PubSub/Presence check).
  • Export VM metrics: run :telemetry_poller for scheduler utilization and memory.
  • Alert on error rates, DB timeouts, queue depths, and VM memory.

Common Pitfalls

  • Building releases without PHX_SERVER=true (endpoint won’t start).
  • Missing runtime config in config/runtime.exs; relying on compile-time config for secrets.
  • No cluster discovery configured → Presence inconsistencies across nodes.
  • Leaving default secret_key_base or per-node keys → invalid sessions after deploy.
  • Large assets without digests/CDN → slow cold loads.

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 Phoenix Ops AI skill do?

Phoenix operations and deployment: releases, runtime configuration, clustering, libcluster, telemetry/logging, secrets, assets, background jobs, and production hardening on the BEAM.

Why use Phoenix Ops on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/bobmatnyc/claude-mpm-skills/tree/main/toolchains/elixir/ops/phoenix-ops. 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 Phoenix Ops?

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 Phoenix Ops?

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

Is the Phoenix Ops AI skill free?

Yes. It is published on GitHub by bobmatnyc 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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