ENGINEERING

File a Linear license-review ticket for risky model adds

When a PR introduces a Hugging Face model with a non-permissive or unknown license, it opens a Linear issue assigned to the legal-review team with the model, license.

CategoryEngineering
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerPull request opened with model changesGitHubGitHub
  • ActionExtract added HF model IDs from diffGitHubGitHub
  • ActionResolve license and gated statusHugging FaceHugging Face
  • LogicRoute only risky or unknown licenses
  • OutputCreate Linear license-review issueLinearLinear

What it does

Turns a borderline license into a tracked review task instead of a blocking wall. When a Hugging Face model dependency lands with a copyleft, custom, gated, or missing license, this workflow creates a Linear issue so a human reviewer can make the call, with all the context already gathered.

When to use it

Use it when your policy is "escalate, don't auto-block" — teams that want legal or eng-lead sign-off on questionable licenses rather than a hard merge gate. Pairs well with a hard-block workflow that handles the clearly-forbidden cases.

How it works

  1. 1A GitHub pull request event triggers the run.
  2. 2Newly added Hugging Face model IDs are pulled from the diff.
  3. 3The Hugging Face API resolves each model's license and gated status from its model card.
  4. 4A logic step routes only licenses that are non-permissive, custom, gated, or undeclared into the escalation path; clean permissive licenses exit quietly.
  5. 5A Linear issue is created on the license-review team with the model name, license tag, PR author, and PR URL, labeled for triage.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GitHubRepos, issues, pull requests, actions.
  2. 2
    Connect Hugging FaceModels, datasets, spaces — the open-source hub.
  3. 3
    Connect LinearIssues, projects, cycles, triage.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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