---
slug: "skills-wandb"
source_type: "readme"
source_url: "https://cdn.jsdelivr.net/gh/wandb/skills@main/README.md"
repo: "https://github.com/wandb/skills"
source_file: "README.md"
branch: "main"
---
# skills

[![Codex](https://img.shields.io/badge/codex-25%2F34%20(74%25)-yellow)](#benchmarks)
[![Claude Code](https://img.shields.io/badge/claude--code-31%2F34%20(91%25)-brightgreen)](#benchmarks)

<!-- Uncomment to make badges live (requires public repo):
[![Codex](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/wandb/skills/main/.badges/codex.json)](#benchmarks)
[![Claude Code](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/wandb/skills/main/.badges/claude-code.json)](#benchmarks)
-->

Skills to guide Claude Code, Codex, and other coding agents on using the [Weights & Biases](https://wandb.ai) AI developer platform to train models and build agents.

## For model training

- Log metrics and rich media during model training and fine-tuning
- Track model training experiments
- Analyze runs and experiment results to understand how the model is learning
- Tune hyperparameters

## For agent building

- Trace agentic AI applications
- Analyze traces and classify them into failure modes
- Evaluate models with labeled datasets
- Run online evaluations for production monitoring

## Getting Started

```bash
npx skills add wandb/skills
```

Then set your [W&B API key](https://wandb.ai/authorize):

```bash
export WANDB_API_KEY=<your-key>
```

> `npx skills` is a utility for installing skills into major coding agent CLIs. Use `--global` to install for all projects, or `--agent <name>` to target a specific agent. See the [npx skills docs](https://github.com/vercel-labs/skills) for more details.

## Available Skills

<!-- BEGIN SKILL TABLE -->
| Skill                                    | Description                                                                                                                               | Status       |
| ---------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------- | ------------ |
| [`wandb-primary`](https://github.com/wandb/skills/tree/HEAD/skills/wandb-primary/) | Primary W&B skill for broad, mixed-surface W&B project analysis and workflows across runs, Weave, Reports, Signal Builder, and Launch. | experimental |
<!-- END SKILL TABLE -->

## Benchmarks

We maintain Skill Bench in this repository to evaluate public skill changes
across coding agents and task categories. Skill Bench uses W&B Agent Factory as
the eval runtime for task definitions, agent profiles, sandbox execution, and
structured bench rows.

Pull requests run package validation by default. A maintainer can trigger live
Skill Bench runs for larger changes.

Plan a local benchmark without model calls:

```bash
python3 -m skillbench.cli plan \
  --wbaf-root ../WandBAgentFactory \
  --candidate-ref HEAD \
  --skill wandb-primary
```

| Category                      | Tasks | Claude Code (`sonnet4.6`) | Codex (`gpt-5.3-codex`) |
| ----------------------------- | ----- | ------------------------- | ----------------------- |
| Weave analysis                | 26    | 97%*                      | 63%*                    |
| Weave tooling                 | 11    | 95%*                      | 83%*                    |
| Model training                | 8     | 90%*                      | 85%*                    |
| LLM finetuning & RL analysis  | 14    | 72%*                      | 86%*                    |
| Failure & outlier detection   | 8     | 86%*                      | 63%*                    |

*Pass rates are +/- 3%. Many tasks span multiple categories.

## Contributing

See [CONTRIBUTING.md](https://github.com/wandb/skills/blob/HEAD/CONTRIBUTING.md).