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npx claudepluginhub agent-sh/deslop --plugin deslopDetect and remove AI-generated slop from codebases with certainty-based findings and safe auto-fixes.
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:
agentsys install deslop
# 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
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).
| 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 |
/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.
/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.
all (default) - scan entire codebasediff - only files changed in current branch<path> - specific directory or file/deslop --thoroughness=quick # Phase 1 only
/deslop --thoroughness=normal # Phase 1 + 2 (default)
/deslop --thoroughness=deep # All phases
Two layers, two coverage stories:
| Layer | Languages | Detection |
|---|---|---|
Analyzer slop queries (when repo-intel.json present) | JavaScript/TypeScript, Python, Rust, Go, Java | tree-sitter AST: empty error handling per language idiom, tautological assertions across major test frameworks, orphan exports, cliché-name clusters, wrapper towers, single-impl traits, high-bug communities |
| Regex pipeline (always) | JavaScript/TypeScript, Python, Rust, Go, Java | universal patterns (debug statements, trailing whitespace, mixed indentation, placeholder text), language-specific patterns where defined |
Kotlin, C/C++, and Shell files are walked but no language-specific detectors are bundled today; only universal regex patterns apply. Tracked in #27.
MIT
Uses power tools
Uses Bash, Write, or Edit tools
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Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Removes AI-generated code slop from code changes in the current branch
Tactical code cleanup: type strictness, single responsibility, and fail-fast patterns. Detects sloppy code, workarounds, and silent failures.
Codebase vital signs — hotspot detection, ROI-ranked diagnosis, co-change coupling, knowledge risk, and AI provenance tracking
AI-powered code review analysis — Run three-level AI analysis and implement-review-fix loops directly in your coding agent. Works standalone, no server required.
AI-powered codebase modernization assessment - Interactive audit and quick scan skills to identify technical debt, anti-patterns, and quality issues from older AI-generated code
Find and remove dead code across the codebase
Deep repository analysis to realign project plans with actual code reality - discovers drift, gaps, and produces prioritized reconstruction plans
Master workflow orchestrator with autonomous task-to-production automation, quality gates, and multi-agent review
Plugin structure and tool use analyzer - validates plugin.json, MCP tools, and security patterns
Multi-agent iterative code review until zero issues remain
Unified static analysis via agent-analyzer - git history, AST symbols, project metadata, and doc-code sync
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