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 40+ AI slop patterns 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.
40+ 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.
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 which agents introduced the most issues. Teams that enforce a threshold see scores converge upward within 2 to 4 sprints.
| date | score | delta |
|---|---|---|
| Mar 16 | 51 | — |
| Mar 23 | 63 | +12 |
| Mar 30 | 71 | +8 |
| Apr 06 | 79 | +8 |
| Apr 13 | 88 | +9 |
Configure without config files.
Toggle rules, set severity, and adjust thresholds from the dashboard. No JSON required.
| rule | severity | enabled |
|---|---|---|
| swallowed-exception | error | on |
| trivial-comment | warn | on |
| unsafe-assertion | error | on |
| generic-naming | warn | on |
| dead-code | off | off |
Every agent your team uses. One standard they all answer to.
When aislop finds issues it cannot auto fix, it builds a full context prompt and opens the agent that wrote the code. The fix stays in the same loop.
npx aislop fix npx aislop fix --claude npx aislop fix --codex npx aislop fix --cursor npx aislop fix --gemini npx aislop fix --prompt 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.
Install once for your team
One command wires aislop into the agent's native lifecycle. Runtime hooks for Claude Code, Cursor, and Gemini. Rules-only installers for six more agents.
Agent sees findings in real time
As the agent writes, aislop scores every edit. Issues flow back with file path, line number, rule, severity, and fix guidance. Structured feedback, machine-readable, no prose.
Agent self-corrects or stops
The agent fixes what it just broke on the spot. With
--quality-gate enabled, the hook blocks the
session if the project score drops below the captured baseline.
Or 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. One config block, every project, every session.
Add to mcp.json for Claude Desktop, Cursor, Claude Code, or Codex. Stdio transport. Local-only.
How scanaislop 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 | scanaislop engineering standards layer | SonarQube static analysis suite | ESLint / Prettier lint + format stack | CodeClimate code 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 |