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To celebrate, Dascha (daschasara) answered FFmpeg's call for non-AI artwork and drew this piece for us:

Artwork by Dascha (daschasara)

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Some months ago I started working on a small experiment: a specialised LLM assistant for Debian maintainers preparing proposed updates for stable and oldstable.

The aim is not to replace review by the Stable Release Managers, nor to automate away maintainer judgement. It is meant to be a pre-advice tool: something maintainers can use while they are still preparing a proposed update, before sending it to other people to review.

If you’ve uploaded to stable before you may have some experience with our acceptance criteria. Does the version sort correctly? Is the changelog clear enough? Is the delta focused? Are the patches documented? Are the right bugs or CVEs mentioned? Are they of sufficient severity? What is the risk to users of stable? Is there an ABI change hiding in the diff?

These are the sort of checks where a structured first pass can be useful, provided it is treated as advice rather than authority.

To explain what the tool does, what could be more appropriate in an AI age than to ask it?

Describe yourself and your abilities and limitations for a blog post.

It answers:

I’m Debian Stable Update Adviser, a specialised ChatGPT assistant for Debian maintainers preparing proposed updates for Debian stable and oldstable.

My main job is to review a single .debdiff and give practical, policy-aware feedback before a maintainer submits or uploads a proposed update. I focus on whether the update appears suitable for Debian stable or oldstable, especially under the Stable Release Managers’ expectations for minimal, targeted, low-risk changes.

I can inspect a debdiff for Debian changelog quality, including suite, version, bug references, CVE mentions, and rationale. I can check version correctness using Debian dpkg version semantics. I can review packaging changes under debian/, such as patches, maintscripts, symbols files, conffiles, Build-Depends, autopkgtests, and control metadata. I can also group upstream source changes into behavioural and non-behavioural categories, and flag areas that may carry regression risk.

My reports are intended to be concise and useful to maintainers. A typical review includes a quick summary, behavioural and non-behavioural change breakdown, mechanical policy checks, risk assessment, stable-policy checklist, acceptance likelihood, rationale, maintainer advice, and a clear conclusion.

My limitations are important. I cannot prove that a package builds, that tests pass, that the bug is fully fixed, or that the Stable Release Managers will accept the upload. I also do not replace maintainer judgment, archive review, autopkgtest results, reproducibility checks, or real-world upgrade testing. I can only review the provided debdiff and point out likely issues, risks, and improvements.

I also do not proceed without a valid debdiff. The whole point of my review is to assess the actual proposed delta, not to speculate from package names or bug descriptions alone.

In short, I act as a focused pre-review assistant for Debian stable and oldstable proposed updates: useful for catching policy, versioning, changelog, packaging, and regression-risk issues early, but not a substitute for the Debian review process itself.

That last point is an important one. This is not an oracle, and it is not part of the Debian archive machinery. It is a checklist with some language-model assistance, aimed at reading a debdiff and pointing out things that might be worth another look.

I know that commercial AI and LLM tools are not universally welcome in Debian. That is understandable. Debian depends on transparency, human responsibility, licensing clarity, and technical correctness. LLMs have obvious problems in all of those areas. They can be wrong, and worse, they can be wrong in a fluent and plausible way. They are impossible to reproduce and their training is opaque.

But I see this as a useful first pass for a maintainer who is unused to working in stable, and would benefit from a virtual mentor giving their proposal a quick check and reassurance. Perhaps they don’t have a more experienced co-maintainer to ask. Perhaps they are conscious that stable reviews are presently a two-man effort and want to avoid adding round trips to that load. Perhaps they just need some reassurance.

So despite my reservations I am today opening the adviser up for general use, and I’m interested in feedback about how it responds to real world proposals in various states. Most of the examples I have tested with already had a green light, so the value added by the adviser is limited. I would especially be interested in seeing a transcript alongside the submitted debdiff.

Try it out

I would dearly love to build this in a more Debian-ish environment, but for now I’m limited in resources and skill to do that (help is welcome). Until that’s a reality, you can try out the ChatGPT implementation: Debian Stable Update Adviser