I kept losing hours to tangled GitHub issues, so I built a tool to fix it
Every open source contributor knows this moment: you open an issue to fix a small bug, and it links to another issue, which links to a PR, which references two more issues in a completely different repo — and forty minutes later you have fourteen tabs open and you've forgotten what you were even trying to do.
That happened to me enough times that I finally built something for it.
What FicCrunch does
You paste in one GitHub issue or PR link. FicCrunch crawls the linked issues and PRs it connects to — across repos, not just within one — and gives you back two things:
- A reading order — what to read first, second, third, so you're not guessing
- A visual graph — the actual shape of how everything connects
The crawl is bounded, not infinite. It's not trying to summarize the entire internet about your issue — it's mapping the specific thread you're standing in.
A real example
I ran it on a currently-open Kubernetes tracking issue (kubernetes/enhancements#5526, Pod Level Resource Managers). It correctly traced the full picture across three repos — the KEP, the alpha/beta implementation PRs, and the docs — and it also surfaced something genuinely useful: why the feature got disabled in Beta, tracing back to an unresolved CPU Manager conflict still being worked on. That's the kind of context that normally takes real digging to piece together by hand.
Why structure first, AI optional
FicCrunch doesn't require AI to work. The link graph and reading order are built from the actual GitHub data — no hallucination risk, nothing to double-check. AI summaries are available as an optional layer on top, if you want them, but the core tool works without ever calling a model.
Try it
It's free to use: ficcrunch.com
I'm building this solo as a side project, so if you try it on a gnarly issue of your own, I'd genuinely love to hear how it goes — what it got right, what it missed, what you wish it did differently.
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