wandb-experiment-tracker
SkillDev toolsWeights & Biases integration skill for experiment tracking, hyperparameter sweeps, and artifact versioning.
Use wandb-experiment-tracker in Claude, ChatGPT or Ahel Desktop
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Also: Claude Code · Cursor · Codex
Then ask your AI: use the wandb-experiment-tracker skill
Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
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Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/data-science-ml/skills/wandb-experiment-tracker/SKILL.md and read by Ahel’s review.
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
{
"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
{
"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
{
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
}
}
}
}
Signals
- GitHub stars
- 2k
- Forks
- 113
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
wandb-experiment-tracker- Source
- github.com/a5c-ai/babysitter