gsc-cli

Unfortunately I won't be able to use the npm as I need it for synching which is managed by https://github.com/gitsense/gsc-cli/tree/staging The only thing that seems to be missing is synching but I have a workaround for that but it won't be near realtime. For example, Pi changes are usually a second or less behind the Pi session log. With txcript, it will probably be 5 seconds which is fine since the use case will mostly revolve around discovery, organizing and inspection.

The code in http://github.com/gitsense/gsc-cli contains over 300 go files and I would say 90% were one shots. I can even prove that they are AI generated since I attribute the AI in each file, as shown in the example below: https://github.com/gitsense/gsc-cli/blob/main/internal/cli/r... Since I don't know go, I can't say which is the best. I am also sure they would not live up to a go experts expectations. I just know that since I don't know go, I would not have been able to create the tool. I can also prove that you can easily maintain AI generated code since I have been expanding and evolving it for over 6 months with pretty much no issues.

I am working on solving the AI Code Provenance problem and I believe my repos may be the first that provides AI code provenance. See the following example: https://github.com/gitsense/gsc-cli/blob/main/internal/cli/r... Notice how the code block header attributes the model. The UUID can be traced to the conversation so everybody can tell exactly how the code came about. For this to work though, you need to use my chat app as it ensures you can't tamper with things if you are truly serious about AI code provenance. I also have a lot more human-focused method which is part of my CLI tool. https://github.com/gitsense/gsc-cli I am currently looking at making pi (https://github.com/earendil-works/pi) support AI code provenance, but for now if you want a more structured way to capture what you have done in an agent session that can be used in c

I created this and I would say glm-4.7 accounts for 80% of the code in https://github.com/gitsense/gsc-cli If you look at a file like: https://github.com/gitsense/gsc-cli/blob/main/internal/cli/r... you can see that I attribute the models used. What I found was 4.7 was not very good at `go` code which was why you started to see `Gemini 3 Flash` in the attributions. 4.7 is what Cerebras provide and for me, speed in iterations is a lot more important. Having played around with MiMo v2.5.0-Pro, I am 100% sure it could have done what Gemini 3 Flash did. There were a few points where I was stuck and needed Sonnet to explain things to me, but I think the dirty secret that Anthropic and OpenAI won't tell you is, if you know how to code, the models are honestly good enough. Based on my experience with MiMo and what others are saying about GLM 5.

FYI your link 404s. Seems like you copied the ellipsified version, so what we get is https://github.com/gitsense/gsc-cli/blob/main/internal/cli/r

This sounds like it is more aligned with what I have created which is "We need to capture your conversations with AI". If you look at https://github.com/gitsense/gsc-cli/blob/main/internal/cli/r... you can see that every file has a code block header with a UUID and the AI that was attributed to it. With the UUID, I can tell exactly how the code came about. What they are working on will be more useful for AI code provenance. It is only a matter of time before you are expected to show your chats with AI as part of the code review and for performance reviews. So I don't see human collaboration being the main use case. I see tracking, studying and improving the Human-AI relationship...and seeing if somebody should be promoted or not. An interesting take I've heard is, we will have a token/impact stat where if you spent a shitload of tokens to

My CLI does something close to this: https://github.com/gitsense/gsc-cli `gsc grep` is just an alias for `gsc rg`, mostly because agents are much more likely to reach for “grep” than “rg”. It works pretty well, but it is not a perfect drop-in replacement. `grep` and `ripgrep` differ in a few details, especially around glob/wildcard behaviour and flags. What I found works is to not use `grep` in search examples, and have the CLI spit out an error message for the AI saying this is `ripgrep`, so it needs to use `ripgrep` syntax.

I was able to create a CLI (https://github.com/gitsense/gsc-cli) without knowing Go. Like 0% Go knowledge. It is currently over 300 files (266 Go files).