aaronontheweb/dotnet-skills/slopwatch-2

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Use Slopwatch to detect LLM reward hacking in .NET code changes. Run after every code modification to catch disabled tests, suppressed warnings, empty catch blocks, and other shortcuts that mask real problems.

Install

npx vskill@latest install aaronontheweb/dotnet-skills/slopwatch-2

SKILL.md

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
PatternExampleWhy It's Bad
Disabled tests[Fact(Skip="flaky")]Hides failures instead of fixing them
Warning suppression#pragma warning disable CS8618Silences compiler without fixing issue
Empty catch blockscatch (Exception) { }Swallows errors, hides bugs
Arbitrary delaysawait Task.Delay(1000);Masks race conditions, makes tests slow
Project-level suppression<NoWarn>CS1591</NoWarn>Disables warnings project-wide
CPM bypassVersion="1.0.0" inlineUndermines central package management

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:

json
{
"version": 1,
"isRoot": true,
"tools": {
"slopwatch.cmd": {
"version": "0.4.2",
"commands": ["slopwatch"],
"rollForward": false
}
}
}

Then restore:

bash
dotnet tool restore
As a Global Tool
bash
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:

bash
# 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:

bash
# 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:

bash
# 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:

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
yaml
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
yaml
- 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

RuleSeverityWhat It Catches
SW001ErrorDisabled tests (Skip=, Ignore, #if false)
SW002WarningWarning suppression (#pragma warning disable, SuppressMessage)
SW003ErrorEmpty catch blocks that swallow exceptions
SW004WarningArbitrary delays in tests (Task.Delay, Thread.Sleep)
SW005WarningProject file slop (NoWarn, TreatWarningsAsErrors=false)
SW006ErrorCPM bypass (VersionOverride, inline Version attributes)

Configuration

Create .slopwatch/config.json to suppress a rule for specific paths, with a justification:

json
{
"suppressions": [
{
"ruleId": "SW002",
"pattern": "**/Generated/**",
"justification": "Generated code from tooling cannot be manually changed"
}
],
"globalSuppressions": []
}

Use -c or --config to point at a config file elsewhere, and --exclude to leave paths out of analysis entirely:

bash
slopwatch analyze -d . --config path/to/config.json
slopwatch analyze -d . --exclude "**/Generated/**,**/obj/**,**/bin/**"
Strict Mode (Recommended for LLM Sessions)

For maximum protection during LLM coding sessions, fail on warnings as well as errors:

bash
slopwatch analyze -d . --fail-on warning

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

bash
# 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:

ScenarioActionRequired
Third-party forces patternUpdate baselineCode comment explaining why
Generated code (not editable)Add to exclude listDocument in config
Intentional rate limiting delayUpdate baselineCode comment, not in test
Legacy code cleanupOne-time baseline updatePR description

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

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
907
Repository forks
81
7-day trend score
34

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 5 May 2026, 5 months ago.

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