Show HN: A lightweight app to let LLM work for oncall

[tanglearncode]

The biggest gap today in SRE agents is missing domain knowledge. So they cannot give accurate results for oncall incident handling. I just didn't find any lightweight and suitable solution to exactly solve the problem. So I created a desktop application NeatContext. It does nothing but can let LLMs know your domain knowledge to handle the incidents right.

[tanglearncode]

I just made a video to show how the domain knowledge issue can be solved: https://youtu.be/lh5ZgP6CHss

[tanglearncode]

A claude code plugin is now open sourced: https://github.com/XTSoftwareLabs/neatcontext-plugins

It extracts domain knowledge and save useful work from a Claude Code conversation as structured, reusable context that you can use in later sessions or share with others.

[tanglearncode]

A little more context on this. I have tried quite a few of SRE agents or AI incident handling assistants in the market. LLMs can help on incident handling if the domain knowledge and context are clear. However, in most of time, they are missed. SRE agents usually are belong to a platform. Naturally the platrom companies want users to keep within them. However, the domain knowledge are anywhere inside user's company. Every team has its own domain knowledge to impact how to handle an incidents in real time. This results inaccurate response from AI.

I'm trying to solve this problem in another approach. Create a lightweight desktop app, let the user connect whatever domain knowledge they have, whether a doc inside company, or runbooks, or TSGs or even some rules within a team only. Let the user connect to their own internal systems. Then provide those context to LLM. It works pretty well.

Here is the hands on demo to show exactly how it works: https://github.com/XTSoftwareLabs/neatcontext-demo

[amit1525]

interesting... keep going