ENGINEERING
Agent-authored license-change impact report to Confluence
When a HuggingFace model's license changes, an agent researches the new terms, assesses commercial-use and redistribution impact across every dependent repo.
How it runs
The automated pipeline, trigger to output.
- TriggerLicense-change webhook receivedHTTP webhook
- ActionFetch full new license terms from model cardHugging Face
- ActionFind dependent repos and usage pathsGitHub
- LogicAssess commercial/redistribution/attribution impact
- ActionPublish impact report to ConfluenceConfluence
- OutputPost Slack summary with report linkSlack
What it does
This workflow turns a raw license change into a decision-ready brief. When a watched HuggingFace model card's license changes, an agent reads the new license text, identifies the practical restrictions (commercial use, redistribution, attribution, derivative limits), maps which of your repos consume the model and how, and writes a structured impact assessment. The finished report is published to Confluence and linked from a Slack heads-up so stakeholders can act.
When to use it
Use it when a license change needs interpretation, not just detection — when leadership needs to understand exposure across the codebase before deciding whether to keep, pin, or rip out a model.
How it works
- 1A HuggingFace model-card license change is detected via webhook.
- 2The agent fetches the full new license terms from the model card.
- 3It queries GitHub to find every repo and code path importing the model.
- 4It reasons over usage to assess commercial, redistribution, and attribution impact.
- 5It publishes a structured impact report to Confluence.
- 6It posts a Slack summary linking the report.
Set it up
What you configure once, before turning it on.
- 1Connect Hugging FaceModels, datasets, spaces — the open-source hub.
- 2Connect GitHubRepos, issues, pull requests, actions.
- 3Connect ConfluenceSpaces, pages, blueprints.
- 4Connect SlackChannels, DMs, threads, mentions.
- 5Connect HTTP webhookTrigger any URL on agent actions.
- 6Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 7Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 8Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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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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