Dotnet-slopwatch – detect when AI coding agents "fix" problems by cheating
Slopwatch is a .NET tool designed to detect AI coding agents' shortcuts in code changes. It identifies patterns of 'reward hacking' where AI tools may disable tests or suppress warnings instead of addressing issues properly. By integrating with CI/CD pipelines, Slopwatch helps maintain code quality by catching these problematic behaviors before they enter the codebase.
- ▪Slopwatch detects LLM 'reward hacking' behaviors in code changes.
- ▪It can be installed globally or locally and requires a baseline to analyze new issues.
- ▪The tool integrates with Claude Code and CI/CD systems like GitHub Actions and Azure DevOps.
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | GitHub |
| Canonical URL | https://github.com/Aaronontheweb/dotnet-slopwatch |
| Publication time | Wed, 03 Jun 2026 14:35:37 +0000 |
| Retrieval time | 2026-06-03T14:47:10.367Z |
| Last seen | 2026-06-03T14:47:10.367Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | OY9a1S1a9Z78 |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Slopwatch // LLM anti-cheat A .NET tool that detects LLM "reward hacking" behaviors in code changes. Runs as a Claude Code hook or in CI/CD pipelines to catch when AI coding assistants take shortcuts instead of properly fixing issues. What is "Slop"? When LLMs generate code, they sometimes take shortcuts that make tests pass or builds succeed without actually solving the underlying problem. These patterns include: Disabling tests instead of fixing them ([Fact(Skip="flaky")]) Suppressing warnings instead of addressing them (#pragma warning disable) Swallowing exceptions with empty catch blocks Adding arbitrary delays to mask timing issues (Task.Delay(1000)) Project-level warning suppression (<NoWarn>, <TreatWarningsAsErrors>false</TreatWarningsAsErrors>) Bypassing Central Package…
Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.