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lora-training

lora-training is a skill for Claude Code from runcomfy-com/skills. It costs 52 tokens per session (811 once invoked), scanned A, original, MIT.

A helper for preparing data and managing LoRA training on RunComfy GPUs. LoRA training adapts an existing AI model using examples so it can learn a particular subject or style.

In plain words
What is it for?
Use it to inspect or upload datasets, check their readiness, review training configuration, start approved jobs, monitor progress, and retrieve checkpoints or samples.
Why use it?
It helps verify that the dataset, captions, base model, training settings, and budget are suitable before starting a paid training job.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the runcomfy plugin — 4 skills, 1 MCP server shipped together

not rated 15repo +3 17d ago A scan 52 tokens original MIT

Good fit Use it to inspect or upload datasets, check their readiness, review training configuration, start approved jobs, monitor progress, and retrieve checkpoints or samples.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/runcomfy-com/skills/lora-training
View source ↗ runcomfy-com/skills
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 runcomfy-com/skills --skill lora-training
Clone the repo
git clone --depth 1 https://github.com/runcomfy-com/skills

Made for: Claude Code.

Or install runcomfy, the plugin that ships this one along with the rest of its 4 skills, 1 MCP server.

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 lora-training

README.md
[![agentmods](https://agentmods.dev/badge/skills/runcomfy-com/skills/lora-training/github.svg)](https://agentmods.dev/skills/runcomfy-com/skills/lora-training)
Your own site
<a href="https://agentmods.dev/skills/runcomfy-com/skills/lora-training"><img src="https://agentmods.dev/badge/skills/runcomfy-com/skills/lora-training/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 lora-training

Your own site · 80×15
<a href="https://agentmods.dev/skills/runcomfy-com/skills/lora-training"><img src="https://agentmods.dev/badge/skills/runcomfy-com/skills/lora-training.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 811 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 $0.00052 $0.00811
Opus 5.5 $0.00021 $0.00324
Sonnet 5.5 $0.00010 $0.00162
Haiku 4.5 $0.00005 $0.00081

Measured 16d ago against content hash f823a4d4f62e, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-02, from the pricing page.

Security

Grade A, and why

lora-training 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 16d 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.

plugins/runcomfy/skills/lora-training/SKILL.md · 36 lines

How it starts

The opening of the file, as written. The whole thing — 36 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Train and retrieve a LoRA with RunComfy

Use the connected RunComfy MCP tools. If disconnected, use the client's authentication flow; do not request tokens in chat. Explaining LoRA settings alone does not require creating a dataset or starting a job.

Prepare a reproducible configuration

  1. Establish the user's training purpose, base model, dataset, desired output and spending limit. Verify supported base-model/trainer settings in current RunComfy documentation or the user's known working AI Toolkit config. An inference model's availability does not imply that it supports training.
  2. Use list_datasets to find the intended dataset. For a new dataset, create and upload files only within the user's authorization. Preserve exact filenames and matching caption names.
  3. upload_dataset_file_from_url imports media from an accessible URL; upload_dataset_text_file writes caption text. For local files, get_dataset_upload_urls provides signed upload destinations. Upload through a supported client tool without exposing signed URLs or credentials in prose. If no upload tool is available, explain that limitation.
  4. Verify the resulting file inventory and get_dataset_status readiness before submission. Do not treat upload acceptance as a READY dataset.
  5. Prepare the complete AI Toolkit YAML from verified configuration, including model/adapter compatibility, steps, learning rate, rank, batch size, resolution, checkpoint interval and sample settings. Use a unique job name consistently across the YAML. Do not silently rename an existing job or resume it.
  6. Respect the platform path contract: training_folder is /app/ai-toolkit/output; dataset folder_path is /app/ai-toolkit/datasets/{dataset_name} using its name, not ID. These are remote container paths, not files to create on the user's computer.
  7. Check current GPU options/rates and get_balance. Show the exact YAML, GPU type/count, dataset, estimated cost, spending limit and monitoring/stop conditions. Proceed only with the user's approval of that concrete run; previously approved unchanged settings do not need repeated confirmation.

Read the full file on GitHub · 36 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. 16d ago First seen · 36 lines · 52 tokens per session scan A f823a4d4f62e

Subscribe to this mod's changes

lora-training is a skill published in the GitHub repository runcomfy-com/skills (15 stars, last pushed 17d ago), licensed MIT. It adds 52 tokens to every session and 811 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-16.

Creative and mediaData and AI
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