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wandb-experiment-tracking

wandb-experiment-tracking is a skill for Claude Code, Codex from dongzhuoyao/tao-research-skills. It costs 67 tokens per session (2,395 once invoked), scanned A, original, no licence file.

A guide for adding Weights & Biases, a service for recording and viewing machine-learning training experiments, to training pipelines.

In plain words
What is it for?
Setting up run configuration, choosing a logging strategy, managing online and offline modes, and using W&B calls such as wandb.init and wandb.log.
Why use it?
It helps decide what training data to record and how runs should work online or offline.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

not rated 10repo 4mo ago A scan 67 tokens no licence

Good fit Setting up run configuration, choosing a logging strategy, managing online and offline modes, and using W&B calls such as wandb.init and wandb.log.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/dongzhuoyao/tao-research-skills/wandb-experiment-tracking
View source ↗ dongzhuoyao/tao-research-skills
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add dongzhuoyao/tao-research-skills --skill wandb-experiment-tracking
Clone the repo
git clone --depth 1 https://github.com/dongzhuoyao/tao-research-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for wandb-experiment-tracking

README.md
[![agentmods](https://agentmods.dev/badge/skills/dongzhuoyao/tao-research-skills/wandb-experiment-tracking/github.svg)](https://agentmods.dev/skills/dongzhuoyao/tao-research-skills/wandb-experiment-tracking)
Your own site
<a href="https://agentmods.dev/skills/dongzhuoyao/tao-research-skills/wandb-experiment-tracking"><img src="https://agentmods.dev/badge/skills/dongzhuoyao/tao-research-skills/wandb-experiment-tracking/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for wandb-experiment-tracking

Your own site · 80×15
<a href="https://agentmods.dev/skills/dongzhuoyao/tao-research-skills/wandb-experiment-tracking"><img src="https://agentmods.dev/badge/skills/dongzhuoyao/tao-research-skills/wandb-experiment-tracking.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 67 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,395 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00067 $0.02395
Opus 5.5 $0.00027 $0.00958
Sonnet 5.5 $0.00013 $0.00479
Haiku 4.5 $0.00007 $0.00239

Measured 2mo ago against content hash ded4e3d59be9, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

wandb-experiment-tracking scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

W&B pages are JavaScript-rendered SPAs. `WebFetch` or `curl` on a W&B URL returns empty HTML with no data. Always use the Python API:
skills/experiments/wandb-experiment-tracking/SKILL.md · 283 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2mo ago First seen · 283 lines · 67 tokens per session scan A ded4e3d59be9

Subscribe to this mod's changes

wandb-experiment-tracking is a skill published in the GitHub repository dongzhuoyao/tao-research-skills (10 stars, last pushed 4mo ago), with no licence file. It adds 67 tokens to every session and 2,395 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Analytics and metricsData and AI
Related

wandb-experiment-tracking compared with skills from other repositories

wandb-experiment-tracking next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
wandb-experiment-trackingdongzhuoyao/tao-research-skillsSkill104mo agononeA67Claude Code, Codex
agent-platform-model-registrygoogle/skillsSkill22kyesterdayApache-2.0A60Claude Code, Codex
foundry-config-setupmicrosoft/agent-frameworkSkill15kyesterdayMITA65Claude Code, Codex
google-cloud-solution-agentic-analytics-spark-knowledge-cataloggoogle/skillsSkill22kyesterdayApache-2.0A132Claude Code, Codex
training-checkwanshuiyin/Auto-claude-code-research-in-sleepSkill19k3d agoMITA35Claude Code
nemo-automodel-launcher-configNVIDIA/skillsSkill3.9kyesterdayApache-2.0A30Claude Code
finetuningmicrosoft/skillsSkill3.2kyesterdayMITA132Claude Code