本文へ移動
cccskills
無料GitHub で公開

onboard-marin

Verify or complete a new internal Marin developer's local setup and access to GitHub, GCP, Iris, Weights & Biases, Hugging Face, and optional CoreWeave storage. Use when a team member asks to onboard, validate onboarding, or diagnose missing development access.

インストール方法を見る

含まれるファイル(1)

  • SKILL.md4.2 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Onboard a Marin developer

Establish which parts of the developer environment are ready, fix local setup when safe, and identify each missing external grant. Keep secrets out of command output and the final report.

Sources

Use these as the current sources of truth:

  • Local installation: docs/tutorials/installation.md.
  • Development workflow: docs/dev-guide/contributing.md.
  • Iris authentication and access checks: lib/iris/OPS.md and the use-iris skill.
  • CoreWeave credentials and routing: docs/tutorials/cloud-gpu.md.
  • Pulumi operator grants and state access: infra/pulumi/README.md, the add-grant skill, and the review-grant skill.

Do not copy procedures from infra/README.md; it is an infrastructure index.

Verify

Start with read-only checks. Report each area as ready, missing access, missing local setup, or not checked.

  1. Confirm the command is running from a Marin checkout and inspect the working tree without changing user work.
  2. Check the required local tools and Python version. Check dependency and pre-commit setup against the installation and contributing guides. Install or repair local dependencies when the user's onboarding request authorizes it.
  3. Check GitHub authentication and repository push permission without pushing a branch.
  4. Check the active GCP account, the hai-gcp-models project, Application Default Credentials, and read access to gs://marin-us-central2. Confirm the current principal has projects/hai-gcp-models/roles/marindev with a filtered IAM query that prints only the matching role name. Do not print credential contents or the complete project policy.
  5. When the user will operate the marin GCP Pulumi stack:
    • In addition to the marindev check above, confirm the current principal has projects/hai-gcp-models/roles/marinPulumiAdmin with the same filtered IAM query.
    • Check that the Pulumi CLI and repository deploy dependencies are present. Run pulumi -C infra/pulumi stack export --stack marin >/dev/null to verify state access without printing state contents.
    • Report CoreWeave kubeconfig access separately when the user will operate a CoreWeave stack. Do not run pulumi up as an onboarding check. Do not grant roles or mutate live IAM unless the user asks for the grant workflow.
  6. Check Iris authentication and read-only cluster status. Use iris login only for an interactive human session; let the browser or headless login flow request the human's input.
  7. Check whether WANDB_API_KEY and HF_TOKEN are present without printing their values. When useful, perform a read-only identity check with the service's CLI and confirm access to the marin-community W&B entity. Do not persist a token outside the user's chosen credential store.
  8. Check CoreWeave object-storage access only when the user needs to inspect GPU job outputs. Do not treat storage credentials as proof of GPU scheduling access; Iris controls compute access separately.

Distinguish local configuration failures from permissions that a maintainer must grant. GCP project access, Iris IAP access, GitHub access, Weights & Biases, Hugging Face, Pulumi operator access, and CoreWeave storage are independent.

Smoke tests

Run local import or CPU checks when they are cheap and do not download a large dataset. A remote Iris job changes shared state: submit one only when the user explicitly authorizes the smoke job. Keep it CPU-only, small, and bounded. Never request a GPU or TPU during onboarding.

Do not start, stop, restart, deploy, or otherwise mutate a shared cluster.

Report

Give the user a compact checklist of verified capabilities and remaining actions. Include the failing command category and error summary without secret values. Distinguish grants the user can request from local fixes. Do not edit IAM data or file a grant request unless the user asks.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Run an explicitly requested Zephyr control/treatment benchmark on the same pre-normalized sample and compare Finelog stage metrics.

日本語の概要は準備中です。原文の説明を表示しています。

marin-community/marin3,9462026年10月13日 更新

Register a named Hugging Face dataset for Marin by inspecting its schema and adding the appropriate experiments/datasets module.

日本語の概要は準備中です。原文の説明を表示しています。

marin-community/marin3,9462026年10月13日 更新

add-grant

無料

Implement a fully specified request for a GCP IAM resource grant or Cloud Run IAP viewer in marin-iac.

日本語の概要は準備中です。原文の説明を表示しています。

marin-community/marin3,9462026年10月13日 更新

Add or change a named Pallas/Mosaic kernel, including its reference implementation, correctness tests, wrapper, or requested tuning.

日本語の概要は準備中です。原文の説明を表示しています。

marin-community/marin3,9462026年10月13日 更新

Archive explicitly named legacy experiment files by publishing a dated tag and canonical issue breadcrumbs.

日本語の概要は準備中です。原文の説明を表示しています。

marin-community/marin3,9462026年10月13日 更新

Launch or continuously monitor a specified Zephyr pipeline on Iris only when asked to babysit it; restart only after explicit approval.

日本語の概要は準備中です。原文の説明を表示しています。

marin-community/marin3,9462026年10月13日 更新

marin-community のスキルをすべて見る

このスキルの問題を報告する