skill
empire-ai-best-practices
Field-tested runbook + Claude Code skill for the Empire AI Alpha cluster: SSH/TOTP auth pattern for agents, Slurm job patterns, H100/H200 map, storage, troubleshooting
Set up
Skills are installed by placing their folder where your agent loads skills.
The download comes from github.com/Chasonnnn/empire-ai-best-practices itself, not from our server, so what you get is exactly what its author published.
Install instructions come from the README
README
synced Oct 26, 2026Empire AI best practices
Agent skill for Empire AI access, environment staging, Slurm jobs, and diagnosis on the Alpha (Hopper/RTX, venvs) and Beta (GB200 NVL72, containers) clusters. The root routes to setup, job operation, Beta specifics, troubleshooting, and dated cluster context.
Assets: job_template.sbatch (Alpha venv job), beta_job_template.sbatch (Beta container job with SIGTERM checkpointing), poll_jobs.sh (single bounded poller), ssh_config, and the legacy BERT smoke submitter.
Account, partition, QoS, storage root, runtime, and workload revisions are explicit inputs. The legacy BERT/SST-2 helper requests one untyped GPU without placement checks, so site policy can override its partition and GPU identity. Use its workload through a guarded project executor; scheduler completion and accuracy alone do not establish the requested hardware. It performs no dependency installation or prior-run deletion.
Install the repository as empire-ai-best-practices in the agent's skill directory, preferably through a symlink to one maintained checkout. See SKILL.md for task boundaries and references/jobs.md for required smoke inputs.
Run local regression checks with the approved Python runtime:
python -m unittest discover -s tests -v
Local checks use fake modules and a fake scheduler. They do not validate live Empire configuration, package compatibility, GPU execution, model/data access, or accuracy.