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agent-sh/deslop

deslop

Detect and remove AI-generated slop from codebases with certainty-based findings and safe auto-fixes.

Why

AI coding tools leave behind debug statements, placeholder text, empty catch blocks, over-commented code, and dead abstractions. Manual cleanup is tedious and error-prone. deslop runs a 3-phase detection pipeline that categorizes every finding by certainty level - HIGH findings get auto-fixed, MEDIUM findings get flagged for review, and LOW findings are reported without action. Behavior is preserved. Diffs are minimal.

Use cases:

  • Pre-PR hygiene - scan changed files before opening a pull request
  • Periodic repo maintenance - sweep the full codebase for accumulated slop
  • CI gate - fail on HIGH-certainty slop in changed files

Installation

agentsys install deslop

Quick Start

# Report slop findings (no changes made)
/deslop

# Auto-fix HIGH certainty findings
/deslop apply

# Scan only changed files in current branch
/deslop report --scope=diff

# Fix up to 10 findings in a specific directory
/deslop apply src/ 10

How It Works

deslop uses a 3-phase detection pipeline with increasing analysis depth:

Phase 1 - Regex patterns (HIGH certainty). Fast pattern matching for console.log, print(), dbg!(), TODO/FIXME markers, empty catch blocks, hardcoded secrets, trailing whitespace, and mixed indentation. These are safe to auto-fix.

Phase 2 - Multi-pass analyzers (MEDIUM certainty). Structural analysis for doc-to-code ratio problems, verbose over-commenting, over-engineering, buzzword inflation, dead code after return/throw, and stub functions. These need human review.

Phase 3 - CLI tools (LOW certainty, optional). Runs external tools when available - jscpd for duplication, madge for circular dependencies, eslint/pylint/clippy/golangci-lint for language-specific issues. Findings are flagged but not auto-fixed.

Thoroughness levels control which phases run:

Level Phases Speed
quick Phase 1 only Seconds
normal (default) Phase 1 + 2 Seconds
deep Phase 1 + 2 + 3 Depends on CLI tools

Repo-intel integration - when repo-intel data is available, deslop targets AI-written files first (recent-ai query) and escalates MEDIUM findings to HIGH for files with no test coverage (test-gaps query).

Certainty Levels

Level Meaning Action
HIGH Definitely slop - safe to remove Auto-fixed in apply mode
MEDIUM Likely slop - needs context Flagged for review
LOW Possible slop - context-dependent Reported only

Usage

Report Mode (default)

/deslop
/deslop report --scope=diff
/deslop report --thoroughness=deep

Outputs a prioritized table of findings with certainty levels and suggested fixes. No files are modified.

Apply Mode

/deslop apply
/deslop apply --scope=diff
/deslop apply src/ 10

Auto-fixes all HIGH certainty findings, then runs the project's test suite. If tests fail, all changes are rolled back with git restore . and the failing fix is reported.

Scope Options

  • all (default) - scan entire codebase
  • diff - only files changed in current branch
  • <path> - specific directory or file

Thoroughness Options

/deslop --thoroughness=quick    # Phase 1 only
/deslop --thoroughness=normal   # Phase 1 + 2 (default)
/deslop --thoroughness=deep     # All phases

Supported Languages

JavaScript/TypeScript, Python, Rust, Go, Java/Kotlin, C/C++.

Requirements

  • Git (required for rollback safety)
  • Node.js
  • agentsys runtime
  • For deep mode: jscpd, madge, eslint, pylint, clippy, or golangci-lint (optional, used when available)

Related Plugins

License

MIT

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AI slop cleanup with minimal diffs and behavior preservation

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