distributed-training-setup

distributed-training-setup is a skill for Claude Code from DamingDong/opencode-skills-hub. It costs 64 tokens per session (434 once invoked), scanned A, original, MIT.

A machine-learning setup assistant for training one model across multiple computers or processors. It provides guidance, code, configurations, and validation results.

In plain words
What is it for?
Use it to prepare distributed training setups, including configuration and implementation guidance for machine-learning projects.
Why use it?
It helps organize the configuration needed when one machine is not enough for model training.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it to prepare distributed training setups, including configuration and implementation guidance for machine-learning projects.

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Install with agentmods
npx agentmods add skills/damingdong/opencode-skills-hub/distributed-training-setup
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 DamingDong/opencode-skills-hub --skill distributed-training-setup
Clone the repo
git clone --depth 1 https://github.com/DamingDong/opencode-skills-hub

Made for: Claude Code.

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 distributed-training-setup

README.md
[![agentmods](https://agentmods.dev/badge/skills/damingdong/opencode-skills-hub/distributed-training-setup/github.svg)](https://agentmods.dev/skills/damingdong/opencode-skills-hub/distributed-training-setup)
Your own site
<a href="https://agentmods.dev/skills/damingdong/opencode-skills-hub/distributed-training-setup"><img src="https://agentmods.dev/badge/skills/damingdong/opencode-skills-hub/distributed-training-setup/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 distributed-training-setup

Your own site · 80×15
<a href="https://agentmods.dev/skills/damingdong/opencode-skills-hub/distributed-training-setup"><img src="https://agentmods.dev/badge/skills/damingdong/opencode-skills-hub/distributed-training-setup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 434 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.
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 $0.00064 $0.00434
Opus 5 $0.00032 $0.00217
Sonnet 5 $0.00013 $0.00087
Haiku 4.5 $0.00006 $0.00043

Measured 6d ago against content hash a471ef195d55, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

distributed-training-setup 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 6d 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.

skills/community/distributed-training-setup/SKILL.md · 73 lines

What it actually says

Distributed Training Setup

Overview

This skill provides automated assistance for distributed training setup tasks within the ML Training domain.

When to Use

This skill activates automatically when you:

  • Mention "distributed training setup" in your request
  • Ask about distributed training setup patterns or best practices
  • Need help with machine learning training skills covering data preparation, model training, hyperparameter tuning, and experiment tracking.

Instructions

  1. Provides step-by-step guidance for distributed training setup
  2. Follows industry best practices and patterns
  3. Generates production-ready code and configurations
  4. Validates outputs against common standards

Examples

Example: Basic Usage Request: "Help me with distributed training setup" Result: Provides step-by-step guidance and generates appropriate configurations

Prerequisites

  • Relevant development environment configured
  • Access to necessary tools and services
  • Basic understanding of ml training concepts

Output

  • Generated configurations and code
  • Best practice recommendations
  • Validation results

Error Handling

Error Cause Solution
Configuration invalid Missing required fields Check documentation for required parameters
Tool not found Dependency not installed Install required tools per prerequisites
Permission denied Insufficient access Verify credentials and permissions

Resources

  • Official documentation for related tools
  • Best practices guides
  • Community examples and tutorials

Part of the ML Training skill category. Tags: ml, training, pytorch, tensorflow, sklearn

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. 6d ago First seen · 73 lines · 64 tokens per session scan A a471ef195d55

Subscribe to this mod's changes

distributed-training-setup is a skill published in the GitHub repository DamingDong/opencode-skills-hub (11 stars, last pushed 7mo ago), licensed MIT. It adds 64 tokens to every session and 434 once invoked, about $0.0003 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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