training-check
Periodically check WandB metrics during training to catch problems early (NaN, loss divergence, idle GPUs). Avoids wasting GPU hours on broken runs. Use when training is running and you want automated health checks.
Profile →npx skills add majiayu000/claude-skill-registry --skill training-check --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Training Check Periodically read WandB metrics during training to catch problems early. Do not wait until training finishes to discover it was a waste of GPU time. > ⏱ This skill is **correctly** cron-wired (see below): it polls > machine-checkable training health (NaN / divergence / idle GPU) — the additive > external-wait shape in > [`shared-references/external-cadence.md`](../shared-references/external-cadence.md). > The occasional Codex call for an ambiguous metric is a **one-shot** check per > tick, not a multi-round verdict loop, so it stays additive — it never grows > into a wrapped verdict skill. ## Context: $ARGUMENTS ## Constants - WANDB_ENTITY and WANDB_PROJECT: read from CLAUDE.md or passed as argument (format: `entity/project/run_id`) - CHECK_INTERVAL: starts at 10 minutes, then gradually increases if consistently healthy: 10 min → 20 min → 30 min → 60 min (cap) - REVIEWER_MODEL = `gpt-5.5` — used via Codex MCP for ambiguous cases only ## When to Use - After training is confirmed running (session alive, loss decreasing for first few steps) - Set up via CronCreate to fire periodically during training - **This skill checks training QUALITY, not process HEALTH.** Proces
- Context: $ARGUMENTS
- Constants
- When to Use
- Workflow
- Step 1: Read WandB Metrics
- Step 2: Judgment
- Step 3: Codex Judgment (only when unsure)
- Step 4: Act
- Integration with Watchdog
- Rules
- CronCreate Setup Example
ssh server "tail -100 /path/to/training.log"
What does the training-check skill do?
Periodically check WandB metrics during training to catch problems early (NaN, loss divergence, idle GPUs). Avoids wasting GPU hours on broken runs. Use when training is running and you want automated health checks.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill training-check --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.