AI AGENTS
Weekly HuggingFace Fleet License Audit with GitLab MR Rollup
Sweeps every pinned HuggingFace model across all repos, builds a consolidated license-and-gating posture report.
How it runs
The automated pipeline, trigger to output.
- TriggerWeekly schedule kicks off fleet sweep
- ActionFetch license and gating for all pinned modelsHugging Face
- LogicAggregate posture table and compute weekly delta
- ActionLLM writes executive change summaryOpenAI
- OutputOpen GitLab MR updating compliance ledgerGitLab
What it does
Provides the wide view: once a week it audits the license and gating status of your entire model fleet, not just one repo. It assembles a consolidated posture table, has an LLM write an executive summary of what changed and why it matters, and opens one rollup GitLab MR updating the canonical compliance ledger so leadership and auditors review the whole picture in a single place.
When to use it
Use it for a recurring compliance cadence where you need a periodic, signed-off record of fleet-wide model licensing rather than per-model alerts. Pairs well with the real-time watchers for day-to-day catches.
How it works
- 1A weekly schedule kicks off the fleet sweep.
- 2Fetch license and gating metadata for every pinned model across all tracked repos from HuggingFace.
- 3Aggregate into a posture table and compute the delta versus last week's ledger.
- 4Have an LLM write an executive summary of notable changes and their compliance impact.
- 5Open a single GitLab MR updating the compliance ledger with the table and summary attached.
Set it up
What you configure once, before turning it on.
- 1Connect Hugging FaceModels, datasets, spaces — the open-source hub.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect GitLabRepos, MRs, pipelines, registry.
- 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 AI Agents workflows
Custom Metrics Cardinality Spike Pager
A webhook from a Datadog monitor fires when custom-metric cardinality jumps; an agent pinpoints the offending metric and tag, estimates the added cost.
Sentry-to-Confluence Runbook Updater
When a Sentry issue is resolved, the agent finds the matching Confluence runbook page and proposes an inline update with the verified fix.
Stale Doc-PR Chaser for Runbook Gaps
On a daily schedule the agent finds runbook doc PRs that were opened from resolved incidents but never reviewed, summarizes what each one fixes.
Resolved Incident to Public Troubleshooting Doc
For customer-facing errors resolved in Sentry, the agent drafts a sanitized troubleshooting entry and opens a PR to your ReadMe documentation.
On-Call Runbook Gap Closer: Resolved Sentry Issues to Doc PRs
An agent reads each newly resolved Sentry issue, compares the actual fix against your existing runbook, and opens a GitHub PR adding the missing remediation steps.
Weekly On-Call Doc-Gap Digest
Each week the agent reviews every Sentry issue resolved in the last 7 days, ranks the ones whose runbook coverage is missing or thin.
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.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.
