Generic AI reviewers don't know what your repo is. SlopBuster does — and it changes everything about what a good review looks like.

Getting Started

How It Works

SlopBuster is a codebase-aware AI code reviewer that understands your repository, detects AI-generated issues, and explains findings in context.

The fundamental principle

Without knowing what a repo is, a good code review cannot happen. Every other tool reviews your diff against generic rules. SlopBuster first builds a structured understanding of your repo — then reviews the diff against that understanding.

Phase 0: RepoWatch — Building Your Quality Profile

Before any PR is reviewed, RepoWatch runs a structured discovery sequence. These checks are mandatory — they gate everything else:

main-development-branch → Which branch is the integration target?

main-languages → Not just "Python" — which version? 3.9 and 3.13 need completely different advice.

what-is-the-repo-about → Web API? Embedded firmware? ML pipeline? Game engine? This changes everything.

RepoWatch then assembles a repo_intelligence block that gets prepended to every review prompt:

Repository: tacticaledge/prospectory-backend

Stack: Python 3.13 | FastAPI, Pydantic V2, SQLAlchemy

Goals: High test coverage, Schema-first contracts, Type safety

Quality Profile (12 assessments):

architecture: Dependency injection pattern confirmed (excellent)

security: No hardcoded secrets found (good)

testing: Integration tests present, unit coverage low (needs_attention)

Skip these folders: tests/outputs/, docs/_build/

The Fog of War system progressively reveals checks relevant to your domain using expert personas — Raymond Hettinger for Python projects, Rob Pike for Go services, domain experts for embedded, ML, or blockchain repos. Checks are revealed 1–3 at a time. Never overwhelming. Always specific.

Phase 1: The PR Review — 3 Bots in Parallel

When a PR is opened, three specialized bots run simultaneously — each with the repo_intelligence block loaded:

Code Review Bot

Reviews architecture, patterns, maintainability, and adherence to your codebase standards. Catches framework reinvention against full repo grep access.

Slop Checker Bot

Has full repo grep access. Specifically hunts for AI-generated patterns: reimplemented utilities, hallucinated APIs, band-aid fixes that ignore existing solutions.

Security Review Bot

Change-scoped security analysis: injection, secrets, auth, input validation — with domain-specific interpretation based on what the repo is.

Phase 2: Findings & Teaching Chat

SlopBuster shows 1–3 issues at a time, prioritized by impact. Every finding includes a teaching chat grounded in your codebase — ask why it matters, how to fix it, what the better pattern is. The answer uses your code as the example, not a generic Stack Overflow snippet.

11 Quality Pillars

Every check belongs to one of 11 pillars. Each check has domain-specific interpretations — “input validation” means sensor bounds for embedded firmware, SQL parameter binding for a web API, schema validation for an ML pipeline.

Know Yourself

Discovery: stack, languages, versions, repo purpose

Architecture

Layering, dependency direction, module boundaries

Maintainability

Naming, complexity, duplication, modularity

Testing

Coverage, test types, meaningful assertions

Security

Injection, secrets, auth, input validation

Performance

Algorithmic complexity, N+1s, memory budgets

Resilience

Error handling, retries, graceful degradation

Observability

Logging, tracing, alerting

Deployment & Operations

CI/CD, rollback, environment parity

Team Practices

PR hygiene, commit quality, documentation

AI Collaboration

Prompt contracts, structured output, no keyword band-aids