wandb-experiment-tracker

Weights & Biases integration skill for experiment tracking, hyperparameter sweeps, and artifact versioning.

509 stars

Best use case

wandb-experiment-tracker is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Weights & Biases integration skill for experiment tracking, hyperparameter sweeps, and artifact versioning.

Teams using wandb-experiment-tracker should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

You only need a quick one-off answer and do not need a reusable workflow.
You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/wandb-experiment-tracker/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/data-science-ml/skills/wandb-experiment-tracker/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/wandb-experiment-tracker/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How wandb-experiment-tracker Compares

Feature / Agent	wandb-experiment-tracker	Standard Approach
Platform Support	Not specified	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

Weights & Biases integration skill for experiment tracking, hyperparameter sweeps, and artifact versioning.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# wandb-experiment-tracker

## Overview

Weights & Biases integration skill for experiment tracking, hyperparameter sweeps, artifact versioning, and team collaboration.

## Capabilities

- Experiment logging and visualization
- Hyperparameter sweep configuration and execution
- Artifact versioning and lineage tracking
- Table and media logging (images, audio, video)
- Team collaboration features
- Report generation and sharing
- Model registry integration
- Custom visualization dashboards

## Target Processes

- Model Training Pipeline with Experiment Tracking
- Experiment Planning and Hypothesis Testing
- Model Evaluation and Validation Framework

## Tools and Libraries

- Weights & Biases (wandb)

## Input Schema

```json
{
  "type": "object",
  "required": ["action"],
  "properties": {
    "action": {
      "type": "string",
      "enum": ["init", "log", "sweep", "artifact", "alert", "report"],
      "description": "W&B action to perform"
    },
    "project": {
      "type": "string",
      "description": "W&B project name"
    },
    "runConfig": {
      "type": "object",
      "properties": {
        "name": { "type": "string" },
        "tags": { "type": "array", "items": { "type": "string" } },
        "notes": { "type": "string" },
        "config": { "type": "object" }
      }
    },
    "logData": {
      "type": "object",
      "properties": {
        "metrics": { "type": "object" },
        "step": { "type": "integer" },
        "commit": { "type": "boolean" }
      }
    },
    "sweepConfig": {
      "type": "object",
      "properties": {
        "method": { "type": "string", "enum": ["grid", "random", "bayes"] },
        "metric": { "type": "object" },
        "parameters": { "type": "object" }
      }
    },
    "artifactConfig": {
      "type": "object",
      "properties": {
        "name": { "type": "string" },
        "type": { "type": "string" },
        "path": { "type": "string" }
      }
    }
  }
}
```

## Output Schema

```json
{
  "type": "object",
  "required": ["status", "action"],
  "properties": {
    "status": {
      "type": "string",
      "enum": ["success", "error"]
    },
    "action": {
      "type": "string"
    },
    "runId": {
      "type": "string"
    },
    "runUrl": {
      "type": "string"
    },
    "sweepId": {
      "type": "string"
    },
    "artifactId": {
      "type": "string"
    },
    "artifactUrl": {
      "type": "string"
    }
  }
}
```

## Usage Example

```javascript
{
  kind: 'skill',
  title: 'Log training metrics to W&B',
  skill: {
    name: 'wandb-experiment-tracker',
    context: {
      action: 'log',
      project: 'ml-experiments',
      runConfig: {
        name: 'resnet-v1',
        tags: ['baseline', 'resnet'],
        config: { lr: 0.001, epochs: 100 }
      },
      logData: {
        metrics: { loss: 0.5, accuracy: 0.85 },
        step: 10
      }
    }
  }
}
```

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