Launching today
Osloq
An AI agent that reproduces GitHub issues for you
42 followers
An AI agent that reproduces GitHub issues for you
42 followers
Most AI dev tools just read your code and guess. Osloq actually runs it. Connect your GitHub, pick an issue, and an AI agent spins up a real sandbox, clones your repo, runs it, and tries to reproduce the bug the way a developer would. You get a report backed by real evidence. What happened, the steps it took, and whether the bug is real, not a hallucinated guess. No local setup, no "works on my machine." It handles the tedious reproduction step so you jump straight to fixing.
hey, product hunt! 👋
i'm enes, solo founder of osloq.
this came from a problem every developer knows too well. someone files a bug report, and before you can even think about fixing it, you drop what you're working on, dig through the repro steps, get your project into the exact state they described, and run it over and over just to confirm the bug is even real. half the time it ends in "works on my machine" and the issue sits there for weeks.
so i built osloq to do that part. you hand it a github issue, and it spins up a real sandbox, clones and runs your actual repo, and tries to reproduce the bug the way a developer would. then it hands you a report backed by real evidence. what it did, what happened, and whether the bug is actually real.
the hardest part while building it was trust. early on the agent would "reproduce" bugs that weren't real, basically confident hallucinations. so a lot of the work went into making it run real code and prove what it found, instead of guessing from reading the source. if it can't back a claim with evidence, it says so.
it's live today and i'd genuinely love your feedback. what would make this useful in your workflow? ask me anything, i'll be here all day.
The "spins up a real sandbox, clones and runs your actual repo" step is the hard part — most repros only fire with real env config, not just the issue text. To get a project runnable, does Osloq read a devcontainer/Dockerfile/build script or infer the setup itself? And for bugs that need secrets or a seeded DB, how is private-repo access scoped — a short-lived token per run, or standing access?
great question! yeah that's the hard part. no devcontainer needed, the agent works out the setup from the repo itself, installs, runs, and iterates until it's up. for bugs that need real config you can add project secrets, encrypted and only decrypted inside the sandbox, never logged, and if a secret turns out to be invalid or a service can't be reached (say an expired token or a bad db url), it can swap in a local stand-in to still reach the reported code path. access is through the github app with a short-lived token per run, nothing standing
Foyer
Reproducing issues is genuinely one of the more annoying parts of the bug triage loop, especially when the report is half-baked and the reproducer assumes environment context the submitter forgot to mention. Curious how Osloq handles that case. When the issue is ambiguous or missing key details, does the agent ask clarifying questions, make assumptions and document them, or just fail gracefully and tell you what it couldn't figure out? Also wondering whether the reproduced case outputs something like a failing test or a script, or just a description of the steps it took.
Really smart move focusing the agent on reproducing issues specifically, instead of trying to fix everything. Repro is the annoying part that eats up so much of my morning, and getting a clean repro is half the battle anyway.