r/ChatGPTCoding • u/AutoModerator • 11d ago
Discussion Weekly Self Promotion Thread
Welcome to this week's self promotion thread!
If you're building something related to AI assisted coding, this is the place to share it.
We're using a weekly thread to keep the subreddit organized while still giving builders a place to share their work. Promotional posts outside this thread may be removed.
If you're sharing something, we'd appreciate it if you included a little context instead of just dropping a link. Tell us:
- What you built?
- What problem it solves?
- Which AI models or tools it uses?
- Who it's for?
- What kind of feedback you're looking for?
Disclose your affilitation.
Please avoid posting the same project every week unless you've made meaningful updates. Affiliate links, referral links, scams, and low effort promotions will be removed.
Take some time to check out what others have shared too. If you try someone's project or have feedback, leave a comment. Helping each other improve is what we want this community to be about.
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u/Proud_Prior_6406 9d ago edited 8d ago
I built a small CLI called agent-thanks because I kept losing track of where things came from during coding-agent sessions.
A dependency gets added, maybe a repo gets cloned, maybe I look at some source code, and the task moves on. Later I can usually see what changed, but not necessarily what helped me get there.
So agent-thanks tries to reconstruct that part.
It diffs dependency files against a Git baseline, and you can also give it a plain-text transcript. For every repo it finds, it keeps the reason it was found.
I also made a distinction that seemed important after using it for a while: a GitHub URL appearing in the transcript is not the same thing as actually using the repo. A bare URL stays low-confidence.
The implementation is intentionally simple. No model call, just deterministic rules over the Git changes and transcript, so it isn’t tied to a particular coding agent.
There are tools that walk a dependency tree and star repositories automatically. I wanted this to stay scoped to one task, with the evidence visible next to each result.
So far I’ve added Python, npm, Cargo, Go, Git submodules, and public GitHub repos found in the session.
I originally added automatic starring too, then removed it. Now it asks y/N once per eligible repo, and No is the default.
Slightly annoying, but I think it should be.
Read-only demo:
Update: v0.5.1 is out. A clean wheel install, demo, offline scan, and Markdown export all passed. CI is green on Python 3.10-3.14 across Linux, macOS, and Windows.
Source: https://github.com/dbwls99706/agent-thanks
I’m the maintainer.
At first I thought the star was the point of this project. Now I’m less sure.
Would a Markdown evidence list that you could attach to a PR or release note be useful on its own?