How aislop catches what your tests don't.
A deterministic engine scores every change 0–100 in under a second, no LLM at runtime. It runs on the keystroke, in CI, and at the commit, and hands failing code back to the agent that wrote it.
The quality gate for teams shipping AI-generated code to production.
Detect AI slop. Enforce one standard across every repo. Keep weak changes out of production. Scan, score, block, then hand unresolved fixes back to the agent with full context.
Catch what compiles fine but ships broken
aislop scans every file for 50+ rules and checks that survive lint, pass tests, and still reach production. Trivial comments, swallowed exceptions, unsafe type assertions, and more.
Block PRs that don't meet your bar, before they reach review
Every pull request gets a score from 0 to 100. Set your threshold once. Any PR that drops below it gets blocked automatically. No manual review required.
Send failing code back to the agent that wrote it, with full context
aislop auto-fixes what's safe. For everything else, it builds a structured prompt with file paths, issue descriptions, and fix guidance, then opens the agent directly.
AI agents produce these patterns every day. None of them fail your tests.
50+ rules and checks for patterns that pass lint, survive tests, and still reach production. No existing tool catches them. They were built for code humans write, not code agents generate.
Browse all patterns →You set the rules. Agents follow.
Define your standard at the org level. Teams inherit it and can only raise it. Every agent in your org is measured against it, on every PR.
Install once. Enforce forever
Connect your GitHub org in two clicks. Every PR gets a score. Every merge below your threshold gets blocked. No exceptions.
| score | 87/100 |
| threshold | 70 |
| issues | 3 warnings, 0 errors |
| files | 12 scanned |
| score | 54/100 |
| threshold | 70 |
| issues | 8 errors, 4 warnings |
| files | 9 scanned |
Watch AI slop disappear.
Track scores per repo, per team, over time. See which PRs moved the needle and where issues concentrate. Teams that enforce a threshold see scores converge upward within 2 to 4 sprints.
| date | score | delta |
|---|---|---|
| May 25 | 51 | — |
| Jun 01 | 63 | +12 |
| Jun 08 | 71 | +8 |
| Jun 15 | 79 | +8 |
| Jun 22 | 88 | +9 |
Configure without editing YAML.
Toggle rules, set severity, and adjust thresholds from the dashboard. Power users can still version-control `.aislop/config.yml` when they need to.
| rule | severity | enabled |
|---|---|---|
| swallowed-exception | error | on |
| trivial-comment | warn | on |
| unsafe-type-assertion | error | on |
| generic-naming | warn | on |
| dead-code | off | off |
Your agent gets feedback before you do.
aislop hooks into Claude Code, Cursor, Gemini, and six more. As your agent writes, aislop scans. Findings flow back with full context and the agent self-corrects before the code hits your repo.
Every agent your team uses. One standard they all answer to.
When aislop cannot auto-fix an issue, it builds a full-context prompt and opens the agent that wrote the code. Fourteen agents supported today, plus --prompt for anything else.
npx aislop fixnpx aislop fix --claudenpx aislop fix --codexnpx aislop fix --cursornpx aislop fix --gemininpx aislop fix --windsurfnpx aislop fix --aidernpx aislop fix --goosenpx aislop fix --ampnpx aislop fix --antigravitynpx aislop fix --deep-agentsnpx aislop fix --kiminpx aislop fix --opencodenpx aislop fix --warpnpx aislop fix --vscodenpx aislop fix --promptOr let the agent call aislop itself
Hooks are push — aislop scans on every edit, no matter what. MCP is pull — the model decides when to call aislop_scan, aislop_fix, aislop_why, or aislop_baseline on its own.
How aislop compares, out of the box.
This matrix compares first-party, ready-to-adopt workflows. It is not counting custom plugin chains, manual policy wiring, or “you can probably script it” workarounds.
Trivial comments, swallowed errors, generic naming, unsafe assertions.
Useful out of the box without stitching together multiple plugins and presets.
Fixes what is safe automatically, then hands the rest off to an agent or engineer.
Blocks merges with an explicit score threshold and review-ready output.
Secrets, unsafe patterns, dependency audit signals, and policy enforcement in one run.
Import boundaries and structural rules that teams can enforce intentionally.
Hierarchical rules and thresholds instead of one flat local config.
Turns unresolved issues into structured prompts for the coding agent your team uses.
Track score movement over time instead of a single pass/fail signal.
SonarQube was designed for humans committing 20–50 lines. AI agents commit hundreds of lines across dozens of files per session. The tooling needs to match the volume.
| Capability | aislopengineering standards layer | SonarQubestatic analysis suite | ESLint / Prettierlint + format stack | CodeClimatecode quality platform |
|---|---|---|---|---|
AI-specific maintainability patterns Trivial comments, swallowed errors, generic naming, unsafe assertions. | supported | not supported | not supported | not supported |
Zero-config CLI onboarding Useful out of the box without stitching together multiple plugins and presets. | supported | partial support | partial support | partial support |
Auto-fix workflow Fixes what is safe automatically, then hands the rest off to an agent or engineer. | supported | not supported | partial support | not supported |
PR quality gate Blocks merges with an explicit score threshold and review-ready output. | supported | supported | partial support | supported |
Security engine Secrets, unsafe patterns, dependency audit signals, and policy enforcement in one run. | supported | supported | partial support | partial support |
Architecture rules Import boundaries and structural rules that teams can enforce intentionally. | supported | partial support | partial support | not supported |
Org → team → project standards Hierarchical rules and thresholds instead of one flat local config. | supported | partial support | not supported | not supported |
Agent handoff workflow Turns unresolved issues into structured prompts for the coding agent your team uses. | supported | not supported | not supported | not supported |
Trend reporting across repos Track score movement over time instead of a single pass/fail signal. | supported | supported | not supported | supported |
Designed for AI-generated code volumes SonarQube was designed for humans committing 20–50 lines. AI agents commit hundreds of lines across dozens of files per session. The tooling needs to match the volume. | supported | not supported | not supported | not supported |
Run it on your repo in one command.
No setup, no LLM, no account. Scan locally, wire hooks for real-time feedback, or connect GitHub to enforce the same bar across every PR.
npx aislop scan