Elixir Code Review logo

Elixir Code Review

Organization
existential-birds
elixir-code-review

Reviews Elixir code for idiomatic patterns, OTP basics, and documentation. Use when reviewing .ex/.exs files, checking pattern matching, GenServer usage, or module documentation.

Overview

Publisherexistential-birds
Repositorybeagle
Skill nameelixir-code-review
Stars
82
Forks
8
Bundled files
4
LicenseApache-2.0
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.

  • 4 bundled files

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

  • Open source

    Published by existential-birds on GitHub. Read the source before you install it.

Installation

Install the Elixir Code Review 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/existential-birds/beagle.git /tmp/beagle
mkdir -p .claude/skills
cp -r /tmp/beagle/plugins/beagle-elixir/skills/elixir-code-review .claude/skills/elixir-code-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Elixir Code Review 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 Elixir Code Review 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 Elixir Code Review 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 Code Review

Quick Reference

Issue TypeReference
Naming, formatting, module structurereferences/code-style.md
With clauses, guards, destructuringreferences/pattern-matching.md
GenServer, Supervisor, Applicationreferences/otp-basics.md
@moduledoc, @doc, @spec, doctestsreferences/documentation.md

Review Checklist

Code Style

  • Module names are CamelCase, function names are snake_case
  • Pipe chains start with raw data, not function calls
  • Private functions grouped after public functions
  • No unnecessary parentheses in function calls without arguments

Pattern Matching

  • Functions use pattern matching over conditionals where appropriate
  • With clauses have else handling for error cases
  • Guards used instead of runtime checks where possible
  • Destructuring used in function heads, not body

OTP Basics

  • GenServers use handle_continue for expensive init work
  • Supervisors use appropriate restart strategies
  • No blocking calls in GenServer callbacks
  • Proper use of call vs cast (sync vs async)

Documentation

  • All public functions have @doc and @spec
  • Modules have @moduledoc describing purpose
  • Doctests for pure functions where appropriate
  • No @doc false on genuinely public functions

Security

  • No String.to_atom/1 on user input (use to_existing_atom/1)
  • No Code.eval_string/1 on untrusted input
  • No :erlang.binary_to_term/1 without :safe option

Valid Patterns (Do NOT Flag)

  • Empty function clause for pattern match - def foo(nil), do: nil is valid guard
  • Using |> with single transformation - Readability choice, not wrong
  • @doc false on callback implementations - Callbacks documented at behaviour level
  • Private functions without @spec - @spec optional for internals
  • Using Kernel.apply/3 - Valid for dynamic dispatch with known module/function

Context-Sensitive Rules

IssueFlag ONLY IF
Missing @specFunction is public AND exported
Generic rescueSpecific exception types available
Nested case/condMore than 2 levels deep

When to Load References

  • Reviewing module/function naming → code-style.md
  • Reviewing with/case/cond statements → pattern-matching.md
  • Reviewing GenServer/Supervisor code → otp-basics.md
  • Reviewing @doc/@moduledoc → documentation.md

Gates — before reporting

Do these in order for the review batch. Do not publish findings until each step passes.

  1. Protocol loaded — Read review-verification-protocol and apply its checks for each finding category you use (unused, validation, security, performance, etc.). Pass: For every substantive finding, you can name which protocol subsection you satisfied or state N/A with reason (pure style).
  2. Anchored evidencePass: Each finding includes a concrete locator: path:line (or line range), or Module.function/arity plus a short quoted snippet from the file.
  3. Claims backed by artifacts — For assertions like unused code, missing validation, or security risk, Pass: You attach the supporting artifact (e.g. search results, file read scope) or downgrade the item to an explicit question / uncertain with what you did not verify.

Before Submitting Findings

Complete Gates — before reporting (section above) first; the verification protocol is mandatory input to those gates.

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 Elixir Code Review AI skill do?

Reviews Elixir code for idiomatic patterns, OTP basics, and documentation. Use when reviewing .ex/.exs files, checking pattern matching, GenServer usage, or module documentation.

Why use Elixir Code Review on TypingMind?

Because you install it once and use it with any model. Elixir Code Review 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 Elixir Code Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/existential-birds/beagle/tree/main/plugins/beagle-elixir/skills/elixir-code-review. 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 Elixir Code Review?

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 Elixir Code Review?

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

Is the Elixir Code Review AI skill free?

Yes. It is published on GitHub by existential-birds under the Apache-2.0 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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