Use W&B Skills ↗

Documentation Index#

Fetch the complete documentation index at: https://docs.wandb.ai/llms.txt Use this file to discover all available pages before exploring further.

Install W&B Skills to teach your coding agent how to train models, build agents, and analyze experiments using W&B’s AI development platform.

W&B Skills are reusable instruction sets that teach coding agents how to use W&B effectively. Instead of manually guiding your agent through W&B APIs and best practices, install Skills so that the agent can work with experiment tracking, tracing, evaluations, and monitoring on its own.

Skills work with several major coding agents, including:

• Claude Code
• Codex
• Cursor
• GitHub Copilot
• Gemini CLI

For a full list of supported agents, see the W&B Skills CLI documentation.

W&B Skills capabilities#

Skills covers both the W&B Models SDK (training runs, metrics, artifacts, sweeps) and the Weave SDK (traces, evaluations, scorers). Includes helper libraries, reference docs, and data analysis patterns.

Prerequisites#

Skills requires the following:

• Node.js (for the npx command).
• A W&B API key. Create one at wandb.ai/authorize and then set it as an environment variable:

  export WANDB_API_KEY=<your-api-key>

• (Optional) Set your W&B project name as a WANDB_PROJECT environment variable. This allows your agent to target the correct W&B project without you specifying it each time.

Install W&B Skills#

To install W&B Skills globally, run the following command with the --global flag:

npx skills add wandb/skills --skill '*' --yes --global

To install Skills for a specific project, run the following command from your project directory:

npx skills add wandb/skills --skill '*' --yes

You can also install Skills for specific agents using the --agent flag:

npx skills add wandb/skills --agent claude-code --skill '*' --yes --global

For list of --agent and --skill options, see the skills CLI documentation.

Use W&B Skills#

Once installed, you can ask the agent to perform W&B-related tasks for your project. The following example prompts demonstrate some of the tasks your agent can do with W&B Skills:

• “Log training metrics for my PyTorch model to W&B.”
• “Analyze the loss curves for my last 10 runs and identify the best performing configuration.”
• “Trace my LangChain agent and log the results to Weave.”
• “Run an evaluation on my agent using the test dataset and summarize the results.”
• “Find the failure modes in my last evaluation and classify them.”
• “Compare the configs of run A and run B and show me the differences.”

Usage tips#

Skills performs better when you use more specific queries versus broader open-ended questions. The following table provides some recommended example prompts versus prompts that are too vague.