ENGINEERING
Warn the engineer in Slack when a model license is non-commercial
On a PR that adds a Hugging Face model, it checks the license and, if it is non-commercial or research-only, sends the PR author a direct Slack message explaining the restriction…
How it runs
The automated pipeline, trigger to output.
- TriggerPull request opened or updatedGitHub
- ActionExtract added HF model IDs from diffGitHub
- ActionFetch model card licenseHugging Face
- LogicDetect non-commercial or research-only license
- OutputDM the PR author in SlackSlack
What it does
Gives engineers fast, friendly feedback the moment they add a model with a usage-restricted license. Rather than a silent CI failure, the author gets a Slack DM that names the model, the exact license, why it is a problem for a commercial product, and a nudge toward compliant options.
When to use it
Use it on teams that prefer coaching over gatekeeping, where most license mistakes are honest and a quick heads-up resolves them before review. It reduces back-and-forth in PR comments and educates engineers on license policy in context.
How it works
- 1A GitHub pull request event starts the workflow.
- 2The diff is parsed for newly added Hugging Face model IDs.
- 3Each model's license is fetched from its Hugging Face model card.
- 4A logic step matches licenses against a non-commercial and research-only set (for example cc-by-nc, openrail with use restrictions, llama-community terms).
- 5When a match is found, a Slack direct message goes to the PR author with the model, license, plain-English restriction, and permissive alternatives to consider.
Set it up
What you configure once, before turning it on.
- 1Connect GitHubRepos, issues, pull requests, actions.
- 2Connect Hugging FaceModels, datasets, spaces — the open-source hub.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More Engineering workflows
Agent reviews model-license fit and suggests compliant swaps on the PR
When a PR adds a Hugging Face model, an agent reads the model card and license, judges fit against your commercial-use policy.
Block PRs that add incompatible Hugging Face model licenses
When a pull request adds or bumps a Hugging Face model dependency, it fetches the model card license, checks it against your org's allowed-license policy.
Quarterly Logging Hygiene Audit Agent
An agent-driven quarterly sweep that surveys all Axiom datasets, builds a logging-hygiene scorecard per service.
Post-Merge Log Volume Recheck After Downsampling PR
After a log-level PR merges, waits a day then re-queries Axiom to confirm the targeted stream's volume actually dropped.
Axiom Ingest Cost Spike to Linear Triage Ticket
When Axiom ingest volume spikes beyond its baseline, identifies which service caused it and files a Linear ticket with the offending log stream, sample lines, and a downsampling…
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.
Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.

Run this workflow in your colony.
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