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The easiest health checkup for your codebase. Like a blood test for your code — get a full diagnostic report, catch hidden bugs, vulnerabilities, and code quality issues in minutes. We give your agent skills, not pills!
When we first launched LetMeCheck, we believed the biggest problem was helping teams identify code quality issues.
After speaking to more founders, agencies, freelancers, and developers, we realized the real challenge runs much deeper.
The problem isn’t just finding issues.
The real challenge is confidently shipping AI-generated code at scale.
Today, AI tools like Claude, Cursor, and ChatGPT help teams ship incredibly fast. But speed often comes with hidden technical debt: bugs, security risks, poor test coverage, complexity, and fragile architecture.
That’s where the blood test analogy became very real for us.
A blood test doesn’t fix your health.
It helps you understand what’s happening inside before problems become serious.
That’s exactly what LetMeCheck does for your codebase.
This relaunch is built around everything we learned from our users.
LetMeCheck now helps you:
→ Analyze your codebase
→ Check for hidden issues
→ Generate custom AI skill files for your coding agents
→ Fix issues faster
→ Rescan and track improvements
The most exciting part of this launch is custom skill generation.
You can now generate project-specific skills for coding agents so they better understand your code quality standards, avoid repeating mistakes, and produce better outputs with less rework and token waste.
Our mission is simple:
Help teams move from working code to confident code.
Because in the AI era, writing code is becoming easy.
Maintaining quality is the real challenge.
We’re excited to hear your thoughts and feedback 🚀
The custom skill generation is the interesting part. Most code-quality tools produce a report the developer has to internalize and remember to apply next time. Piping the diagnostic back into the agent as project-specific skills is a more honest loop, the agent produced the fragility, the agent gets the fix.
Building MotionFy solo with Cursor, the pattern I keep hitting isn't obvious bugs (those get caught fast) but subtle drift, the codebase slowly starts violating conventions I established in month one because the agent doesn't remember them and I don't re-prompt them. That's the class of debt that gets expensive later, and it's exactly what a project-specific skill pack should catch.
Curious about the closed-loop metric side, when you rescan and detect "measurable improvement," what's the definition? Reduction in specific issue types, LOC of hotspot code, or something else? Trying to figure out if the skill packs actually train the agent or just prevent recurrence of the last problem.
seems like strong to delve deep into security. But the what’s the difference between a skill that checks security + fable 5 vs your app?
How does it actually detect the hidden stuff - is it running static analysis, LLM-based review, or some combo of both under the hood?
ran it against a side project and it flagged a sneaky sql injection i had missed in a rush. the skill pack idea is clever, feels like a real feedback loop instead of a one-off linter.
About LetMeCheck.ai on Product Hunt
“The blood test for AI-generated codebases”
LetMeCheck.ai was submitted on Product Hunt and earned 17 upvotes and 10 comments, placing #21 on the daily leaderboard. The easiest health checkup for your codebase. Like a blood test for your code — get a full diagnostic report, catch hidden bugs, vulnerabilities, and code quality issues in minutes. We give your agent skills, not pills!
LetMeCheck.ai was featured in SaaS (43k followers), Software Engineering (42.7k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 80.2k products, making this a competitive space to launch in.
Who hunted LetMeCheck.ai?
LetMeCheck.ai was hunted by Joel Andriyas - AI First Developer. 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 LetMeCheck.ai stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Joel Andriyas - AI First Developer