wandb-experiment-tracker

SkillDev tools

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

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the wandb-experiment-tracker skill

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
112
Last commit
Sep 2026
Advanced
Item type
skill
Key
wandb-experiment-tracker
Source
github.com/a5c-ai/babysitter