Screened · automated checks passed
hyperpod-slurm-debugger
What the author says it does
Diagnostic-only skill for Slurm scheduler and node-daemon issues on Amazon SageMaker HyperPod Slurm clusters. Scope mirrors the HyperPod troubleshooting guide. Invoke when the user reports a Slurm node stuck in down/drain, "Node unexpectedly rebooted" after auto-repair, slurmd not running, jobs stuck PENDING with REASON=Resources while sinfo shows idle nodes, jobs stuck COMPLETING after node replacement, GRES/GPU counts wrong, scontrol ping failing, slurmctld unresponsive, an Action:Reboot/Replace request that did not trigger HyperPod auto-recovery, or auto-resume not restarting a job. Also triggers on "drain before reboot", "diagnose a Slurm node", "investigate stuck jobs.
Quoted from the skill's own SKILL.md trigger description — this is what tells
Claude when to activate it. Not yet verified by us.
Automated screening
100/100 validator score
Scored by the same rules as our free SKILL.md validator: trigger description quality, body substance, structure. Automated — a human bench test is the next step in the pipeline.
Install (unverified — review first)
git clone https://github.com/awslabs/agent-plugins # skill lives at: plugins/sagemaker-ai/skills/hyperpod-slurm-debugger/SKILL.md
SkillProof status
This skill is in our test queue. We install every skill in a clean environment, run a trigger battery and score output against a baseline before it earns a catalog page — the full protocol is public. Until then, treat it like any unreviewed dependency: read the SKILL.md and any scripts before installing.
Already tested in Productivity & Workflow
- Fetch URL As Markdown Local trafilatura-first URL-to-Markdown fetcher with a clean exit-code contract for when to fall back to Exa.
- Refresh Context Map Rebuilds the AIDEV-anchor/AGENTS.md/ADR manifest that powers claude-leverage's PreToolUse context hook.
- Video Vision Local ffmpeg+Whisper pipeline that lets Claude actually watch and transcribe video files
- YT Digest Turns a YouTube URL into a timestamped, screenshotted markdown research note via real yt-dlp + ffmpeg.