ml-stack-hub

Manage Hugging Face or repository artifacts when a user asks to browse revisions, inspect cards, upload files, commit, open a PR, create a discussion, configure a webhook, or publish a model, dataset,

SKILL.md

GitHub

Hub and repository lifecycle

Require artifact type and ID, exact revision, intended operation, license and metadata, visibility, files, provenance, destination, and explicit approval for every write or external notification.

Workflow

  1. Resolve model, dataset, Space, or repository identity to an exact URL and revision; distinguish mutable main branches from immutable commits/tags.
  2. Inspect cards, metadata, license, README, file manifest, and existing provenance before proposing changes.
  3. Keep traces and sensitive artifacts private by default; redact secrets and personal data.
  4. Treat uploads, commits, PRs, discussions, webhooks, publication, and visibility changes as separate approval-gated operations. If no matching runtime operation exists, return a bounded plan with exact API/CLI intent and expected response.
  5. Hand immutable URLs, hashes, metadata, and approval evidence to ml-stack-deployment or ml-stack-audit.

Outputs and abstention

Never claim a write, PR, discussion, webhook, or publication occurred without an observed result. Abstain when revision, license, destination, or approval is missing. Next owner: ml-stack-deployment for serving release, ml-stack-tracking for private traces, or ml-stack-audit for final artifact reconciliation.

See Hub revisions, cards and metadata, repository and PR policy, and trace privacy.