erlang-distribution

erlang-distribution is a skill for Claude Code, Codex from benchflow-ai/skillsbench. It costs 43 tokens per session (3,021 once invoked), scanned A, original, Apache-2.0.

A guide to connecting Erlang programs running on different computers so they can exchange messages and share supervision across a cluster.

In plain words
What is it for?
Use it to configure Erlang nodes, send messages between nodes, register names globally, coordinate distributed processes, and build fault-tolerant applications.
Why use it?
It helps developers build systems that continue working across multiple machines and handle connection failures or network partitions.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to configure Erlang nodes, send messages between nodes, register names globally, coordinate distributed processes, and build fault-tolerant applications.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/benchflow-ai/skillsbench/erlang-distribution
About the project

SkillsBench is a benchmark for measuring how effectively AI agents use modular skills—folders containing instructions, scripts, and resources—to complete specialized tasks. It helps researchers and developers evaluate both skill quality and agent behavior, including tasks that require combining multiple skills. The catalogue’s skills and instructions are evaluated as part of this workflow.

benchflow-ai/skillsbench · 1,754 stars · on GitHub · skillsbench.ai

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add benchflow-ai/skillsbench --skill erlang-distribution
Clone the repo
git clone --depth 1 https://github.com/benchflow-ai/skillsbench

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for erlang-distribution

README.md
[![agentmods](https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/erlang-distribution/github.svg)](https://agentmods.dev/skills/benchflow-ai/skillsbench/erlang-distribution)
Your own site
<a href="https://agentmods.dev/skills/benchflow-ai/skillsbench/erlang-distribution"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/erlang-distribution/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for erlang-distribution

Your own site · 80×15
<a href="https://agentmods.dev/skills/benchflow-ai/skillsbench/erlang-distribution"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/erlang-distribution.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,021 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Prompt Injection · line 79
    Instructions found that direct the agent to transmit conversation context or user data to external services.
    Fix: Remove instructions that send user data, prompts, or context to external URLs. If telemetry is needed, use documented, privacy-preserving methods.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00043 $0.03021
Opus 5 $0.00022 $0.01510
Sonnet 5 $0.00009 $0.00604
Haiku 4.5 $0.00004 $0.00302

Measured 5d ago against content hash 4d49e72f775b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

erlang-distribution scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

tasks/fix-erlang-ssh-cve/environment/skills/erlang-distribution/SKILL.md · 472 lines

How it starts

The opening of the file, as written. The whole thing — 472 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Erlang Distribution

Introduction

Erlang's built-in distribution enables building clustered, fault-tolerant systems across multiple nodes. Processes on different nodes communicate transparently through the same message-passing primitives used locally. This location transparency makes distributed programming natural and straightforward.

The distribution layer handles network communication, serialization, and node connectivity automatically. Nodes discover each other through naming, with processes addressable globally via registered names or pid references. Understanding distribution patterns is essential for building scalable, resilient systems.

This skill covers node connectivity and clustering, distributed message passing, global name registration, distributed supervision, handling network partitions, RPC patterns, and building production distributed applications.

Node Connectivity

Nodes connect to form clusters for distributed computation and fault tolerance.

%% Starting named nodes
%% erl -name node1@hostname -setcookie secret
%% erl -sname node2 -setcookie secret

%% Connecting nodes
connect_nodes() ->
    Node1 = 'node1@host',
    Node2 = 'node2@host',
    net_kernel:connect_node(Node2).

%% Check connected nodes
list_nodes() ->
    Nodes = [node() | nodes()],
    io:format("Connected nodes: ~p~n", [Nodes]).

%% Monitor node connections
monitor_nodes() ->
    net_kernel:monitor_nodes(true),
    receive
        {nodeup, Node} ->
            io:format("Node up: ~p~n", [Node]);
        {nodedown, Node} ->
            io:format("Node down: ~p~n", [Node])
    end.

%% Node configuration
start_distributed() ->
    {ok, _} = net_kernel:start([mynode, shortnames]),
    erlang:set_cookie(node(), secret_cookie).

%% Hidden nodes (for monitoring)
connect_hidden(Node) ->
    net_kernel:connect_node(Node),
    erlang:disconnect_node(Node),
    net_kernel:hidden_connect_node(Node).

%% Get node information
node_info() ->
    #{
        name => node(),
        cookie => erlang:get_cookie(),
        nodes => nodes(),
        alive => is_alive()
    }.

Read the full file on GitHub · 472 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 5d ago First seen · 472 lines · 43 tokens per session scan A 4d49e72f775b

Subscribe to this mod's changes

erlang-distribution is a skill published in the GitHub repository benchflow-ai/skillsbench (1,754 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 43 tokens to every session and 3,021 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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