This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
An AI code reviewer with a senior engineer's memory of your codebase. It knows who calls what and which service depends on it, so it reviews the change, not just the diff.
Context Goblin started as an internal tool. Coding agents produce far more code
than anyone can review by hand, and every reviewer we tried read the diff without
reading what depends on it.
What's in it today:
- Call graph per repo, so it reviews the change against its real callers
- Cross-repo map: routes, queues, shared tables and packages between your services
- Customizable review agents for your specific needs
- Bring your own MCP servers for ticket and org-specific context
- GitHub App
Happy to answer anything about how the context pipeline works.
The call graph is the right unit. The worst bug we shipped this year was in a file I'd never opened and I approved that PR twice, and no diff-only reviewer was ever going to catch it. What I'd want on this page is the false positive rate, because a bot that leaves a comment on every PR gets muted by week two and then it's worse than nothing. Also dynamic dispatch and reflection are where call graphs go quiet, so does it tell me it couldn't resolve a caller, or does it just say nothing?
the cross-repo call graph is the interesting part here, most PR reviewers stop at the diff. how fresh does that map stay as services evolve - is it rebuilt on every push, or something you have to periodically re-sync? asking because a stale map that confidently tells you "nothing downstream depends on this" seems worse than no map at all.
About Context Goblin on Product Hunt
“The quality check for AI-built software”
Context Goblin was submitted on Product Hunt and earned 11 upvotes and 3 comments, placing #14 on the daily leaderboard. An AI code reviewer with a senior engineer's memory of your codebase. It knows who calls what and which service depends on it, so it reviews the change, not just the diff.
Context Goblin was featured in Software Engineering (43k followers) and GitHub (41.4k followers) on Product Hunt. Together, these topics include over 35.9k products, making this a competitive space to launch in.
Who hunted Context Goblin?
Context Goblin was hunted by Clemens Losbichler. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Context Goblin stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Clemens Losbichler