fine-tuning-expert

fine-tuning-expert is a skill for Claude Code, Codex from paperclipai/companies. It costs 45 tokens per session (139 once invoked), scanned A, original, no licence file.

A guide for adapting large language models to specialised tasks using custom training data and methods such as LoRA, a way to train a smaller set of model parameters.

In plain words
What is it for?
Use it to prepare JSONL datasets, configure LoRA or QLoRA training, apply RLHF or DPO, and quantise models.
Why use it?
It helps tailor a model to specific data or behaviour and manage choices such as training settings and model size.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit Use it to prepare JSONL datasets, configure LoRA or QLoRA training, apply RLHF or DPO, and quantise models.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/paperclipai/companies/fine-tuning-expert
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 paperclipai/companies --skill fine-tuning-expert
Clone the repo
git clone --depth 1 https://github.com/paperclipai/companies

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 fine-tuning-expert

README.md
[![agentmods](https://agentmods.dev/badge/skills/paperclipai/companies/fine-tuning-expert/github.svg)](https://agentmods.dev/skills/paperclipai/companies/fine-tuning-expert)
Your own site
<a href="https://agentmods.dev/skills/paperclipai/companies/fine-tuning-expert"><img src="https://agentmods.dev/badge/skills/paperclipai/companies/fine-tuning-expert/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 fine-tuning-expert

Your own site · 80×15
<a href="https://agentmods.dev/skills/paperclipai/companies/fine-tuning-expert"><img src="https://agentmods.dev/badge/skills/paperclipai/companies/fine-tuning-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 139 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 unknown 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 $0.00045 $0.00139
Opus 5 $0.00023 $0.00069
Sonnet 5 $0.00009 $0.00028
Haiku 4.5 $0.00005 $0.00014

Measured 9d ago against content hash 3635b5c5a233, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

fine-tuning-expert 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 9d 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.

fullstack-forge/skills/fine-tuning-expert/SKILL.md · 15 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

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. 9d ago First seen · 15 lines · 45 tokens per session scan A 3635b5c5a233

Subscribe to this mod's changes

fine-tuning-expert is a skill published in the GitHub repository paperclipai/companies (870 stars, last pushed 5mo ago), with no licence file. It adds 45 tokens to every session and 139 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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