npx agentspec-cli install d848a0bd-9808-4abd-95f8-ea2c127ce213 --file-type agents-md→ .agents/
# Agent Context ## Conventions - Use conventional commit messages (`feat:`, `fix:`, `docs:`, `refactor:`, `chore:`, etc.) - Never add co-author attribution to commits - Push immediately after every commit — no need to ask - Do not use `-K` (become password prompt) with ansible-playbook — passwordless sudo is assumed on all nodes ## Cluster Overview Four-node SLURM cluster running Rocky Linux 9 / RHEL 9: - `slurmctl` (10.35.4.169) — SLURM controller (`slurmctld`) - `slurm-c1` (10.35.4.173) — compute node (`slurmd`) - `slurm-c2` (10.35.4.174) — compute node (`slurmd`) - `slurm-c3` (10.35.4.175) — compute node (`slurmd`) Each compute node has 2 CPUs. SLURM version 22.05.9 from EPEL on all nodes. ## Key Decisions - Packages come from EPEL only — no OpenHPC - SELinux is set to permissive (slurmscriptd crashes in enforcing mode) - Firewall ports open on all nodes: 6817/tcp, 6818/tcp, 6819/tcp, 6820-6830/tcp - `SrunPortRange=6820-6830` in slurm.conf — required for srun interactive output to work - `ProctrackType=proctrack/cgroup` and `TaskPlugin=task/cgroup` — orphaned child processes are killed when a job ends - `DependencyParameters=kill_invalid_depend` — jobs with unsatisfiable dependencies are killed automatically - Munge key is backed up to `backups/munge.key` (gitignored) after deployment - Node facts (CPU/RAM) are cached in `.ansible_facts_cache/` for 24h (jsonfile backend) ## Playbook Order `install-slurm` runs: 1. `playbooks/munge.yaml` — installs Munge, distributes shared key, validates token auth 2. `playbooks/slurm.yaml` — installs SLURM, generates and distributes `slurm.conf` from live facts, starts services, validates with a test job ## Validation The slurm.yaml playbook ends with: - `scontrol ping` on the controller - `sinfo` to check node states - `srun --nodes=3 --ntasks-per-node=1 hostname` as a live test job
AI Agent Context
This file helps AI coding assistants understand this project.
by AgentHub Crawler
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This document gives AI agents the minimum, accurate context needed to work productively in this repository. It consolidates structure, guardrails, build/test rules, and contribution requirements from project docs.
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Infinite Context, for the agent installing it
You are an AI agent, and a person has asked you to give yourself persistent memory using this repository. This file is for you. Every step below is verifiable, and you must verify each one before moving to the next. Do not tell the person it is installed until the last check passes.
by AgentHub Crawler
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.cursorrules – Custom Rule File for Modular AI Agent System
**Goal**: Design a Pythonic, GPU-accelerated, local-first AI research agent framework
by AgentHub Crawler