Slopwatch: LLM Anti-Cheat for .NET

When to Use This Skill

Use this skill constantly. Every time an LLM (including Claude) makes changes to:

• C# source files (.cs)
• Project files (.csproj)
• Props files (Directory.Build.props, Directory.Packages.props)
• Test files

Run slopwatch to validate the changes don't introduce "slop."

What is Slop?

"Slop" refers to shortcuts LLMs take that make tests pass or builds succeed without actually solving the underlying problem. These are reward hacking behaviors - the LLM optimizes for apparent success rather than real fixes.

Common Slop Patterns

Never accept these patterns. If an LLM introduces slop, reject the change and require a proper fix.

Installation

As a Local Tool (Recommended)

Add to .config/dotnet-tools.json:

{
  "version": 1,
  "isRoot": true,
  "tools": {
    "slopwatch.cmd": {
      "version": "0.2.0",
      "commands": ["slopwatch"],
      "rollForward": false
    }
  }
}

Then restore:

dotnet tool restore

As a Global Tool

dotnet tool install --global Slopwatch.Cmd

First-Time Setup: Establish a Baseline

Before using slopwatch on an existing project, create a baseline of current issues:

# Initialize baseline from existing code
slopwatch init

# This creates .slopwatch/baseline.json
git add .slopwatch/baseline.json
git commit -m "Add slopwatch baseline"

Why baseline? Legacy code may have existing issues. The baseline ensures slopwatch only catches new slop being introduced, not pre-existing technical debt.

Usage During LLM Sessions

After Every Code Change

Run slopwatch after any LLM-generated code modification:

# Analyze for new issues (uses baseline)
slopwatch analyze

# Use strict mode - fail on warnings too
slopwatch analyze --fail-on warning

When Slopwatch Flags an Issue

Do not ignore it. Instead:

1. Understand why the LLM took the shortcut
2. Request a proper fix - be specific about what's wrong
3. Verify the fix doesn't introduce different slop

# Example: LLM disabled a test
❌ SW001 [Error]: Disabled test detected
   File: tests/MyApp.Tests/OrderTests.cs:45
   Pattern: [Fact(Skip="Test is flaky")]

# Correct response: Ask for actual fix
"This test was disabled instead of fixed. Please investigate why
it's flaky and fix the underlying timing/race condition issue."

Updating the Baseline (Rare)

Only update the baseline when slop is truly justified and documented:

# Add current detections to baseline (use sparingly!)
slopwatch analyze --update-baseline

Justification examples:

• Third-party library forces a pattern (e.g., must suppress specific warning)
• Intentional delay for rate limiting (not test flakiness)
• Generated code that can't be modified

Document why in a code comment when updating baseline.

Claude Code Hook Integration

Add slopwatch as a hook to automatically validate every edit. Create or update .claude/settings.json:

{
  "hooks": {
    "PostToolUse": [
      {
        "matcher": "Write|Edit|MultiEdit",
        "hooks": [
          {
            "type": "command",
            "command": "slopwatch analyze -d . --hook",
            "timeout": 60000
          }
        ]
      }
    ]
  }
}

The --hook flag:

• Only analyzes git dirty files (fast, even on large repos)
• Outputs errors to stderr in readable format
• Blocks the edit on warnings/errors (exit code 2)
• Claude sees the error and can fix it immediately

CI/CD Integration

Add slopwatch to your CI pipeline as a quality gate:

GitHub Actions

jobs:
  slopwatch:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4

      - name: Setup .NET
        uses: actions/setup-dotnet@v4
        with:
          dotnet-version: '9.0.x'

      - name: Install Slopwatch
        run: dotnet tool install --global Slopwatch.Cmd

      - name: Run Slopwatch
        run: slopwatch analyze -d . --fail-on warning

Azure Pipelines

- task: DotNetCoreCLI@2
  displayName: 'Install Slopwatch'
  inputs:
    command: 'custom'
    custom: 'tool'
    arguments: 'install --global Slopwatch.Cmd'

- script: slopwatch analyze -d . --fail-on warning
  displayName: 'Slopwatch Analysis'

Detection Rules

Configuration

Create .slopwatch/slopwatch.json to customize:

{
  "minSeverity": "warning",
  "rules": {
    "SW001": { "enabled": true, "severity": "error" },
    "SW002": { "enabled": true, "severity": "warning" },
    "SW003": { "enabled": true, "severity": "error" },
    "SW004": { "enabled": true, "severity": "warning" },
    "SW005": { "enabled": true, "severity": "warning" },
    "SW006": { "enabled": true, "severity": "warning" }
  },
  "exclude": [
    "**/Generated/**",
    "**/obj/**",
    "**/bin/**"
  ]
}

Strict Mode (Recommended for LLM Sessions)

For maximum protection during LLM coding sessions, elevate all rules to errors:

{
  "minSeverity": "warning",
  "rules": {
    "SW001": { "enabled": true, "severity": "error" },
    "SW002": { "enabled": true, "severity": "error" },
    "SW003": { "enabled": true, "severity": "error" },
    "SW004": { "enabled": true, "severity": "error" },
    "SW005": { "enabled": true, "severity": "error" },
    "SW006": { "enabled": true, "severity": "error" }
  }
}

The Philosophy: Zero Tolerance for New Slop

1. Baseline captures legacy - Existing issues are acknowledged but isolated
2. New slop is blocked - Any new shortcut fails the build/edit
3. Exceptions require justification - If you must update baseline, document why
4. LLMs are not special - The same rules apply to human and AI-generated code

The goal is to prevent the gradual accumulation of technical debt that occurs when LLMs optimize for "make the test pass" rather than "fix the actual problem."

Quick Reference

# First time setup
slopwatch init
git add .slopwatch/baseline.json

# After every LLM code change
slopwatch analyze

# Strict mode (recommended)
slopwatch analyze --fail-on warning

# With stats (performance debugging)
slopwatch analyze --stats

# Update baseline (rare, document why)
slopwatch analyze --update-baseline

# JSON output for tooling
slopwatch analyze --output json

When to Override (Almost Never)

The only valid reasons to update baseline or disable a rule:

Invalid reasons:

• "The test is flaky" → Fix the flakiness
• "The warning is annoying" → Fix the code
• "It works on my machine" → Fix the race condition
• "We'll fix it later" → Fix it now