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ash0ts/public-five-skill-split
Make public PR CI pass when the private WBAF checkout token is unavailable while preserving the manual live benchmark path for maintainers. Co-authored-by: Cursor <cursoragent@cursor.com>
skills
Skills to guide Claude Code, Codex, and other coding agents on using the Weights & Biases 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
npx skills add wandb/skills
Then set your W&B API key:
export WANDB_API_KEY=<your-key>
npx skillsis a utility for installing skills into major coding agent CLIs. Use--globalto install for all projects, or--agent <name>to target a specific agent. See the npx skills docs for more details.
Available Skills
| Skill | Description | Status |
|---|---|---|
wandb-models |
W&B Models skill for runs, sweeps, artifacts, configs, metrics, run history, best-run selection, and model analysis. | experimental |
weave-analysis |
W&B Weave skill for traces, calls, evaluations, scorers, token/cost analysis, and model usage. | experimental |
wandb-reports |
W&B Reports skill for report authoring, workspace guidance, report media, and report/project semantics. | experimental |
signal-builder |
Signal Builder skill for project-grounded monitor and LLM-as-judge signal design. | experimental |
wandb-launch |
W&B Launch skill for queues, jobs, relaunching runs, and remote compute workflows. | experimental |
Benchmarks
We maintain a growing internal benchmark suite that evaluates each skill across coding agents and task categories. The split skills are currently experimental and validated through the W&B Agent Factory benchmark harness.
| 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.
Description
Primary W&B skill for broad or mixed Weights & Biases work: project overviews, W&B runs and artifacts, Weave traces and evaluations, Reports, and Launch…
Languages
Python
99.3%
Shell
0.7%