compute-env-setup SKILL.md skillA
compute-env-setup from pengqianhan/ai-human-research-os is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add pengqianhan/ai-human-research-os/compute-env-setup@git:20260715.38d79bePins git:20260715.38d79be in mdr.lock. Pin the fingerprint instead.
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- Kind
- SKILL.md skill
- Repository
- pengqianhan/ai-human-research-os
- Path
research-skills-hub/claude-science-skills/skills/compute-env-setup/SKILL.md- Versions recorded
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- Latest version
- git:20260715.38d79be, committed Jul 15, 2026
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- License
- MIT
Set up a compute environment on a remote provider so Claude Science jobs can run there. Covers direct SSH/conda hosts, Slurm clusters, container-via-bridge runners, and managed-API providers (Modal, GCP, RunPod). Use when standing up a new provider, porting an env to a different backend, adding a tool that needs its own software stack, or wiring weight caches. Triggers on "new compute provider", "set up env on", "port env to", "build GPU image", "weight cache", "compute_details…
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Setting up compute environments on a remote provider
## Overview
What's invariant across every backend is what a job *needs*: a software stack (specific package versions, often with load-bearing install ordering), possibly some large model weights placed where the tool will find them, and a resource shape. What varies — a lot — is how a given provider materialises those three things and how an env name gets resolved to them at submit time. This skill is about keeping one declarative spec that says *what* the environment is, and treating *how it gets built and addressed on this provider* as something you figure out once per provider. The work ranges from minutes (another conda env on a host that has ten) to days (GPU image + weight cache + egress on a fresh backend), and most of the long tail is diagnosing why the documented invocation doesn't work even though every import succeeds.
**Before building anything:** `compute_details({provider, mode:"read"})`. The env, or a near-match you can extend, may already exist. The doc you get back is also where you'll record what you set up.
## Provider shapes
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How to install
mdr add pengqianhan/ai-human-research-os/compute-env-setup@sha256:83a2e8ae7e29d0d4The line at the top of this page pins the label git:20260715.38d79be, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
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The registry has recorded 1 version of this file, committed on Jul 15, 2026.
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Source
pengqianhan/ai-human-research-os · 3 stars · license MIT · pushed 2026-10-19 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_x2kkpbiuncbqbrhd GET https://markdownregistry.com/api/v1/resolve?ref=pengqianhan/ai-human-research-os/compute-env-setup GET https://markdownregistry.com/api/v1/blob/83a2e8ae7e29d0d413814c759dbf3b3e47f0b08d0251c8f7f2f74f588ccfd276
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