Every team using AI coding agents is quietly accumulating the same debt. The code compiles. Tests pass. The pull request looks fine. And then, three months later, the codebase has a catch block that silently swallows production errors, a TypeScript file gutted by as any casts, and a TODO stub returning hardcoded data to real users.
This is AI slop — and it ships every day, across every team that has adopted Claude Code, Cursor, Copilot, or Codex.
AISlop is the quality gate that catches it before it merges.
TL;DR: AISlop is a free, open-source CLI that scans your codebase for the specific code patterns AI coding agents leave behind. One command:
npx aislop@latest scan. Over 50 checks across 7 languages. Zero API calls. Works offline. It's the linter your AI-assisted workflow has been missing.
What Is AISlop? (And Why Everyone's Talking About It)
AISlop was built by developer Kenny Olawuwo and launched in June 2026 on Dev.to and Hacker News. The premise is simple: AI coding agents have a different failure profile than human developers, and existing linters weren't designed for it.
Your ESLint or Pylint setup catches style violations, unused variables, and syntax errors. What it does not catch is the pattern where an AI agent writes error handling that looks correct but silently swallows failures, or adds type casts that make the compiler quiet without making the code safe.
The tool has 50+ checks across Python, TypeScript, JavaScript, Go, Ruby, Rust, and Java — targeting the exact patterns that AI coding agents produce when they're optimizing for "make the prompt work" instead of "keep this codebase healthy."
In mid-2026, when Cursor, Claude Code, and Copilot have become standard tools in most development workflows, a tool specifically designed for their failure patterns isn't a nice-to-have. It's infrastructure.
Who Is AISlop For?
AISlop is for developers and engineering teams who use AI coding agents regularly and want to keep code quality high without slowing down. Specifically:
- Solo developers using Claude Code or Cursor who want a quick sanity check before committing
- Tech leads reviewing more AI-generated PRs than ever and wanting a first-pass filter
- DevOps engineers looking to add an AI-specific quality gate to CI/CD pipelines
- Freelancers and consultants who want to offer AI code quality auditing as a service
- Open source maintainers receiving agent-assisted contributions from external contributors
If you're writing any code with AI assistance in 2026, AISlop belongs in your workflow.
Key Features of AISlop
50+ Language-Specific Checks
AISlop ships with over 50 checks across 7 languages, targeting patterns specific to AI output: swallowed exceptions, unsafe type casts, dead code and unreachable branches, TODO stubs in production paths, hardcoded environment values, narrative comments, and duplicated helpers. Each check is documented with the why — not just what it catches, but why AI agents produce it.
Zero API Calls, Fully Offline
AISlop runs entirely locally. No API key required. No telemetry. No internet connection needed. This matters for teams with strict data policies and for developers who want a fast pre-commit check that doesn't depend on an external service.
Auto-Fix for Mechanical Issues
Many of AISlop's findings have an auto-fix mode. Run aislop scan --fix and it will automatically resolve the mechanical issues — removing empty catch blocks, stripping narrative comments, converting hardcoded values to environment variable references.
CI/CD Integration Built In
AISlop ships with a dedicated aislop ci command designed for pipeline use. It diffs against a base branch, reports only new findings, exits non-zero on violations, and prints a clean summary that can be posted as a PR comment.
Claude Code Hook Support
Run aislop hook install --claude and AISlop becomes part of your Claude Code workflow automatically. Every session ends with a quality report. You catch the slop before it enters your review queue.
How to Get Started with AISlop in 5 Minutes
Getting AISlop running takes less than the time to read this section:
- Run a scan instantly with no install
npx aislop@latest scan
npx pulls the latest version and scans your current directory. You'll see a scored report in seconds.
- Scan only changed files (recommended for daily use)
npx aislop@latest scan --changes
Limits the scan to files modified since your last commit. Much faster. Ideal for pre-commit hygiene.
- Install as a project dev dependency
npm install --save-dev aislop
Then add "lint:ai": "aislop scan --changes" to your package.json scripts.
- Add it to CI/CD
aislop ci --changes --base origin/main
Drop this into your GitHub Actions or GitLab CI pipeline. PRs with AI slop get blocked automatically.
- Install a Claude Code hook
aislop hook install --claude
AISlop runs automatically after every Claude Code session.
7 Best Use Cases for AISlop
1. Pre-Commit Gate on All AI-Assisted Work
Set aislop scan --changes as a pre-commit hook using Husky. Every developer using Cursor or Claude Code gets a quality report before code enters the review queue. The effect is behavioral: developers start fixing issues before committing rather than letting them accumulate.
2. CI/CD Merge Blocker
aislop ci --changes --base origin/main in your pipeline blocks PRs that contain swallowed exceptions, unsafe casts, or production TODO stubs. No more slop reviews eating code review time.
3. Codebase Debt Audit After Adopting AI Tools
Your team adopted Copilot three months ago. Run aislop scan on the full repo and get a scored baseline report. Use it to prioritize a cleanup sprint before the debt compounds.
4. Open Source Project Quality Control
Before merging agent-assisted contributions, run AISlop on the PR. Maintains quality standards without requiring every reviewer to maintain a mental model of AI failure patterns.
5. Code Quality Consulting Service
Run aislop scan on a client's repository, generate the scored report, and walk them through the findings. Charge $150-$500 per audit. The tool does the scanning; you provide the expertise.
6. Team Onboarding Documentation
Use the aislop report on your own codebase to build a "what not to accept in review" guide for new engineers. Real examples from your own code are more effective than abstract rules, and they're automatically generated.
7. Educational Developer Content
Record your screen running AISlop on a public GitHub repo. Walk through each finding, explain the pattern, and show the fix. High-signal developer content — the tool does the finding, you do the teaching.
5 Copy-Paste Prompts for AISlop
Use these with Claude Code, Cursor, or any AI coding agent after running an AISlop scan.
Prompt 1: Fix a Swallowed Exception
AISlop flagged this catch block in my code: [paste code]. It is swallowing the error and returning an empty array. Rewrite this function to handle the error properly. Log the error with context, surface it to the caller appropriately, and preserve the original stack trace. Show me the fixed version.
Prompt 2: Replace Narrative Comments
AISlop flagged these comments as narrative — they describe what the code does instead of why a decision was made: [paste code with comments]. Rewrite the comments to explain the intent, the constraint, or the non-obvious reason behind each decision. Remove any comment that just restates what the code is already doing.
Prompt 3: Refactor Unsafe Type Casts
AISlop found unsafe casts in my TypeScript file: [paste code]. For each one, suggest the correct type. If the type cannot be determined statically, use unknown with a type guard instead. Show the refactored code with proper types throughout.
Prompt 4: Generate a GitHub Actions Workflow
Write a GitHub Actions workflow file (YAML) that runs npx aislop ci --changes --base origin/main on every pull request targeting main. The job should fail if AISlop reports issues, post a summary comment to the PR with the findings, and pass cleanly when the code is clean.
Prompt 5: Create a Team AISlop Config
Create an aislop.config.js for my team that sets severity thresholds (swallowed exceptions = error, narrative comments = warning, as any = error), excludes the /legacy directory from all checks, and adds a custom rule flagging any console.log left in production code. Write the full config file.
AISlop vs. ESLint: Which Should You Use?
The right answer is both.
ESLint catches style violations, syntax errors, unused variables, and general code quality issues. It was designed for human-written code and is essential regardless of how the code was produced.
AISlop catches patterns that general linters don't model: the specific ways AI coding agents fail when optimizing for task completion rather than codebase health. The two tools are complementary — they don't overlap, they stack. Teams running both catch more issues than teams running either alone.
How to Make Money with AISlop
1. AI Code Quality Auditing
Offer "AI Code Hygiene Audits" to startups and development teams. Run aislop scan on their repository, produce a scored report with prioritized findings, and deliver a consulting session walking through the top issues. Price at $150-$500 per one-time audit, or $300-$800/month for weekly monitoring. Target companies that adopted AI coding tools in the last 6-12 months.
2. CI/CD Integration as a Service
Many teams want AISlop in their pipeline but don't want to spend engineering time on setup. Offer a flat-fee setup service: $500-$1,500 per project, with a $150-$300/month retainer to keep configs updated.
3. Developer Education Products
Create a course or guide series on AI code quality with real examples from AISlop scans. Sell on Gumroad for $29-$99. The product has permanent shelf life — AI coding agent usage is growing, so the slop problem grows with it.
Frequently Asked Questions About AISlop
Is AISlop free?
Yes. AISlop is fully open source and free to use. Run npx aislop@latest scan with no cost and no API key required. The GitHub repo is at github.com/scanaislop/aislop.
Is AISlop safe to use on proprietary code?
Yes. AISlop runs entirely locally with zero API calls and no telemetry. Your code never leaves your machine — safe for NDA projects, enterprise environments, and any project with strict data policies.
What is AISlop best for?
AISlop is best used as a pre-commit gate on AI-assisted work and as a CI/CD merge blocker. It catches the specific patterns AI coding agents produce before they accumulate into technical debt.
How does AISlop compare to Semgrep or SonarQube?
Semgrep and SonarQube are general-purpose static analysis tools. AISlop is purpose-built for AI-generated code patterns. They're complementary — use both. AISlop runs faster, has zero configuration overhead for its target use case, and is free.
Can beginners use AISlop?
Absolutely. The install is npx aislop@latest scan with no configuration needed. The output explains each finding, making it a learning tool as well as a quality gate.
Final Verdict
AISlop solves a problem that wasn't possible to have three years ago. AI coding agents produce a specific, repeatable failure profile that existing linters weren't designed to catch. AISlop was built for exactly that gap.
If you're using Claude Code, Cursor, Copilot, or Codex in 2026 — and you almost certainly are — AISlop belongs in your workflow. The install takes 30 seconds. The first scan will find something. The CI integration takes under 10 minutes. And the impact compounds: every PR that doesn't merge AI slop is a PR that doesn't become technical debt six months from now.
The tool is free, open source, and offline. There's no reason not to try it today.
Want the complete AISlop prompt pack + monetization playbook? I put together a full guide with 10 copy-paste prompts, all 7 use cases mapped out, a complete GitHub Actions workflow, and a step-by-step monetization playbook. Grab it on Gumroad for $9 →
Published: June 25, 2026 | Updated: June 25, 2026
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