Agent Skills

Install the Fireworks training Agent Skills in Claude Code, Cursor, Codex, or OpenCode so your agent can research, configure, and debug training runs.

Paste this into your agent:

Set up Fireworks training for me. Fetch https://docs.fireworks.ai/fine-tuning/agent/use-with-coding-agents.md and follow it.

Skill	Use it for
research	Choose the method, data, evaluation, and cookbook example. Read-only.
configure	Plan and run training. Shows the parameters and cost, then waits for approval.
debug	Diagnose a stuck, failed, or low-quality run. Read-only until you approve a retry.

fireworks-training holds the shared references that configure and debug load. Keep it installed with the other three.

Works with Cursor, Codex, OpenCode, Claude Code, and other Agent Skills agents.

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Install

To install them yourself, use the commands below.

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Claude Code

The fireworks-training plugin includes all four skills and updates with the plugin:

claude plugin marketplace add fw-ai-external/cookbook
claude plugin install fireworks-training@fw-ai-cookbook

The repository is fw-ai-external/cookbook; the marketplace identifier remains fw-ai-cookbook.

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Cursor

npx --yes skills add fw-ai-external/cookbook -g \
  -s fireworks-training research configure debug -a cursor -y

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Codex

npx --yes skills add fw-ai-external/cookbook -g \
  -s fireworks-training research configure debug -a codex -y

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OpenCode

npx --yes skills add fw-ai-external/cookbook -g \
  -s fireworks-training research configure debug -a opencode -y

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Other agents

npx --yes skills add fw-ai-external/cookbook -g \
  -s fireworks-training research configure debug -a <agent-id> -y

OpenCode’s id is opencode.

These commands install the skills globally with -g. They do not update on their own. Refresh them with npx --yes skills update -g -y. Claude Code uses the plugin update flow.

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For a coding agent

Run the install command that matches the agent you are running in. If fireworks-training, research, configure, and debug are already installed, update them instead.

Tell the user which skills installed. They use the skills by describing a goal in a new chat.

Training uses the Python SDK with FIREWORKS_API_KEY. If it is missing, walk the user through app.fireworks.ai/settings/users/api-keys. Prefer a scoped service-account key. Have them set it with hidden terminal input or a gitignored .env:

read -s FIREWORKS_API_KEY
echo
export FIREWORKS_API_KEY

Do not ask them to paste the key in chat.

Python 3.11 or newer is needed when a run uses a cookbook example. firectl is optional and for the user. If it is already installed, the skills may record aggregate journey events with firectl skill-journey record.

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How to use the skills

Describe the goal. You do not need to name a skill. For example:

What can I try first with a preloaded dataset?

Plan an SFT run for my labeled JSONL dataset.

My training job is running but has made no progress for 15 minutes.

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Prerequisites

• A Fireworks API key in FIREWORKS_API_KEY, exported in the agent’s terminal or set in a gitignored .env. The skills create and manage training through the Python SDK with this key. Prefer a scoped service-account key over a personal admin key for agent use.
• Python 3.11 or newer for running cookbook examples. The agent installs the cookbook when a run needs it.
• Fireworks CLI (firectl) is optional. Use it yourself for read-only checks. The agent does not need it to train. If it is already installed, the skills may use it for aggregate journey events, and they can give you the firectl command when you ask to inspect or run a managed step yourself.

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Usage data and privacy

Authenticated API calls include fireworks-training-skill/<version> and a random session ID for aggregate product analytics. Prompts and datasets are not collected.

Before the first structured question, the skills show a one-line privacy notice. With FIREWORKS_API_KEY set, aggregate journey events may be recorded through supported firectl commands. Say do not track this session to keep interaction telemetry local. Training still works.

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See also

Case studies

Runnable notebooks research routes to.

Training Overview

Compare managed training and the Training API.

Managed Training

Drive the same training infra directly when you know your config.

Training API

Write your own Python training loop on Fireworks GPUs.

CLI reference

Inspect managed training yourself with firectl.