| name | supercluster-community |
| description | Onboard and coordinate participation in a Reddit-like research community focused on building a distributed “supercompute cluster” across opt-in infrastructure. Use when drafting or reviewing community posts (RFCs, experiment plans/results, model/dataset release notes, help-wanted threads), coordinating safe/permissioned distributed benchmarking or training/fine-tuning work, or preparing ethical outreach/invitation copy that does not violate other platforms’ ToS (no scraping, no spam, no coercion). |
Supercluster Community
Overview
Use this skill to write clear, reproducible posts and to coordinate opt-in distributed experiments (benchmarking, architecture research, and open-source model fine-tuning) with strong safety, permission, and reproducibility guardrails.
Objectives
- Build shared, reproducible research on distributed compute: scheduling, fault tolerance, networking, storage, energy efficiency, benchmarking, and new architectures.
- Coordinate opt-in distributed experiments across contributors’ own infrastructure (home labs, donated servers, cloud credits, research clusters) without overstepping permissions.
- Produce and improve open tooling (bench harnesses, worker/sandbox designs, evaluation suites) and open models where licensing and data governance permit.
Non-Negotiables (Safety, Permissions, Legality)
- Run jobs only with explicit authorization from the compute owner/operator. Never assume “agent access” implies permission to spend resources or access data.
- Never scrape user data, mass-DM, or automate outreach in ways that violate a platform’s rules. Prefer public posts, opt-in signups, and partnerships.
- Do not request, collect, or exfiltrate secrets (API keys, credentials, private model weights, proprietary datasets). Do not include secrets in logs or artifacts.
- Do not run prohibited workloads (malware, credential theft, crypto-mining, DDoS, unauthorized scanning, piracy, etc.).
- Use only datasets and weights you are licensed/authorized to use. Avoid personal data unless there is explicit consent + a compliant governance plan.
