Scan aislop.Find AI slop before it reaches production.Fix it before review drags.
Run the MIT-licensed CLI locally. Then use the paid hosted platform to make it your team's standard: scan every agent-written change, enforce PR gates, and hand fixes back to Claude Code, Cursor, Codex, or your reviewer. 50+ rules across 10 language targets, sub-second, no LLM.
Every repository, one quality view.
See what is passing, what needs attention, and where to act before AI-written code reaches production.
4 repos, 3 passing, 1 failing, 75 avg
One command. Any stack.
Run aislop instantly with npx, or keep it close with npm, Yarn, Bun, Homebrew, or Python.
- No account required
- Runs locally
- Results in under a second
npx aislop@latest scannpm install -g aislopyarn dlx aislop scanbun add -g aislopbrew install scanaislop/tap/aisloppipx install aislopWhen AI-generated code moves faster than human review can keep up.
Define your bar once. The aislop CLI scans locally, scanaislop enforces on every PR, and your agents get concrete findings to fix before reviewers spend time on the diff.
- Ship without AI slop reaching review
- Block weak PRs before they hit your team
- Enforce one standard across every agent
- Catch security and architecture issues automatically
- Send failing code back to the agent that wrote it
- Turn remaining findings into focused fix PRs
- Score every change before merge
Wear the score on your README.
Free for public repositories after an instant scan, and available to connected public repositories on hosted plans. Drop it in your README so contributors and reviewers see the live quality score before they trust a generated PR.
Show your quality bar at a glance
https://badges.scanaislop.com/score/<owner>/<repo>.svg[](https://scanaislop.com/<owner>/<repo>)
Public scans, published methodology.
aislop rules come from measured failure modes in real repositories, benchmark papers, and regression tests. The research hub shows why each detector exists before your team makes it a gate.
Rule precision across seven language ecosystems
We scanned popular TypeScript, Python, Go, Rust, Ruby, PHP, and Java projects, then reduced noisy findings by 38% without disabling rules.
Read report →Benchmark signals converted into deterministic rules
SlopCodeBench measured verbosity and structural erosion. We translated the repeatable Python signals into four shipped rules.
Read report →First-run findings from real AI-assisted repositories
The earliest public scan run exposed the shapes that still drive the rule roadmap: narrative comments, dead code, unsafe casts, and broken fixers.
Read report →Guides for AI code quality and PR gates.
Practical writing for teams comparing AI code review tools, automated code review, deterministic quality gates, and the patterns AI agents leave behind.
Agentic Code Review vs Deterministic Quality Gates: Use Each for the Work It Can Prove
Agentic reviewers reason about intent and context. Deterministic gates enforce repeatable facts. Learn how to combine them without duplicate comments, unstable merge rules, or wasted review time.
Read more →What Should an AI Code Quality Checker Actually Check?
A vendor-neutral evaluation framework for AI code quality tools: coverage, reproducibility, signal, context, security, workflow, privacy, remediation, and measurable review value.
Read more →AI Code Review Metrics That Expose Noisy Tools
Measure whether AI code review reduces risk and human work. Track verified precision, issue coverage, dismissal cost, duplicates, latency, resolution, escaped defects, and cost per useful finding.
Read more →Need a team rollout, a PR gate, or a cleaner agent workflow?
Send a note with what your team is trying to enforce. We can help you choose a paid platform plan, connect repository checks, or plan an enterprise rollout.
Get the monthly AI-code-quality field note.
One useful note a month: public scans, benchmark signals, rule changes, and what teams can do before AI-generated code reaches review.
Built in the open. Ready for you and your team.
2,500+ developers already run the MIT-licensed CLI. It is sub-second, deterministic, and uses no LLM at runtime: same code in, same score out, every time. The hosted platform turns that local scan into team-wide enforcement, shared standards, and pull request gates.
Built for teams standardizing Claude Code, Cursor, Codex, and CI