training-check
Interactively monitor training metrics from the current Codex session, periodically checking WandB or fallback logs for NaN, divergence, plateaus, and broken runs.
Profile →npx skills add majiayu000/claude-skill-registry --skill training-check-wanshuiyin-auto-claude-code-res --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 You are now in **interactive watch** / 交互式训练监控模式. Keep the current session open and report directly in the current terminal. The user is watching this terminal for updates. By default, run a training health check every 30 minutes, output a concise but complete analysis report after each check, state the next check time, then continue monitoring. This skill checks training **quality**, not basic process health. Process health checks such as whether a tmux session exists or whether the GPU is idle can be handled by watchdog-style tooling; this skill focuses on whether the run is still worth continuing. ## Inputs To Establish First Before the first check, identify or ask for the minimum monitoring context: - WandB run path or URL, if available. - Fallback log path, SSH command, or local command for reading recent training logs. - Training target, expected baseline, and key metrics that define success. - How the training was launched, so it can be stopped if needed. - Project notes path for recording decisions and evidence. If a source is unavailable, say so clearly and continue with the available source. If both WandB and fallback logs are unreachable, report the conn
- Inputs To Establish First
- Per-Round Check
- Stop Behavior
- Interactive Loop Guidance
What does the training-check skill do?
Interactively monitor training metrics from the current Codex session, periodically checking WandB or fallback logs for NaN, divergence, plateaus, and broken runs.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill training-check-wanshuiyin-auto-claude-code-res --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.