sloppylint 0.1.0

Python AI Slop Detector - Find over-engineering, hallucinations, and dead code

🐷 Sloppy

Detect AI-generated code anti-patterns in your Python codebase.

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⚡ Quick Start

# Install from GitHub
pip install git+https://github.com/rsionnach/sloppy.git

# Or clone and install locally
git clone https://github.com/rsionnach/sloppy.git
cd sloppy
pip install -e .

# Run it
sloppy .

# Output:
# CRITICAL (2 issues)
# ============================================================
#   src/api.py:23  mutable_default_arg
#     Mutable default argument - use None instead
#     > def process(items=[]):
#
#   src/db.py:15  bare_except
#     Bare except catches everything including SystemExit
#     > except:
#
# SLOPPY INDEX
# ══════════════════════════════════════════════════
# Information Utility (Noise)    : 24 pts
# Information Quality (Lies)     : 105 pts
# Style / Taste (Soul)           : 31 pts
# Structural Issues              : 45 pts
# ──────────────────────────────────────────────────
# TOTAL SLOP SCORE               : 205 pts
#
# Verdict: SLOPPY

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🎯 What It Catches

The Three Axes of AI Slop

Axis	What It Detects	Examples
📢 Noise	Debug artifacts, redundant comments	print(), # increment x above x += 1
🤥 Lies	Hallucinations, placeholders	def process(): pass, mutable defaults
💀 Soul	Over-engineering, bad style	God functions, deep nesting, hedging comments
🏗️ Structure	Anti-patterns	Bare except, star imports, single-method classes

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📥 What You Put In

# Scan a directory
sloppy src/

# Scan specific files
sloppy app.py utils.py

# Only high severity issues
sloppy --severity high

# CI mode - exit 1 if issues found
sloppy --ci --max-score 50

# Export JSON report
sloppy --output report.json

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📤 What You Get Out

Output	Description
🎯 Issues by Severity	Critical, High, Medium, Low
📊 Slop Score	Points breakdown by axis
📋 Verdict	CLEAN / ACCEPTABLE / SLOPPY / DISASTER
📁 JSON Report	Machine-readable for CI/CD

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🔍 Pattern Examples

Critical Severity

# 🚨 mutable_default_arg - AI's favorite mistake
def process_items(items=[]):  # Bug: shared state between calls
    items.append(1)
    return items

# ✅ Fix: Use None and initialize inside
def process_items(items=None):
    if items is None:
        items = []
    items.append(1)
    return items

# 🚨 bare_except - Catches SystemExit, KeyboardInterrupt
try:
    risky_operation()
except:  # Bug: swallows Ctrl+C!
    pass

# ✅ Fix: Catch specific exceptions
try:
    risky_operation()
except ValueError as e:
    logger.error(f"Invalid value: {e}")

High Severity

# 🚨 pass_placeholder - AI gave up
def validate_email(email):
    pass  # TODO: implement

# 🚨 hedging_comment - AI uncertainty
x = calculate()  # should work hopefully

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💰 The Value

🔍 Catch AI mistakes before they hit production

Why This Matters

Problem	Impact	Sloppy Catches
Mutable defaults	Shared state bugs	✅ Critical alert
Bare except	Swallows Ctrl+C	✅ Critical alert
Placeholder functions	Runtime failures	✅ High alert
Hallucinated imports	ImportError in prod	✅ High alert
JavaScript patterns	.push(), .length errors	✅ High alert
Unused imports	Code bloat	✅ Medium alert
Dead code	Maintenance burden	✅ Medium alert
Copy-paste code	Maintenance nightmare	✅ Medium alert

Research Says

• 40%+ of AI-generated code contains security vulnerabilities
• 20% of AI package imports reference non-existent libraries
• 66% of developers say AI code is "almost right" (the dangerous kind)

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🛠️ CLI Commands

sloppy .                    # 🔍 Scan current directory
sloppy src/ tests/          # 📁 Scan multiple directories
sloppy --severity high      # ⚡ Only critical/high issues
sloppy --lenient            # 🎯 Same as --severity high
sloppy --strict             # 🔬 Report everything
sloppy --ci                 # 🚦 Exit 1 if any issues
sloppy --max-score 50       # 📊 Exit 1 if score > 50
sloppy --output report.json # 📋 Export JSON report
sloppy --ignore "tests/*"   # 🚫 Exclude patterns
sloppy --disable magic_number # ⏭️ Skip specific checks
sloppy --version            # 📌 Show version

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✅ Features

Feature	Description	Status
🔍 Hallucinated Imports	Detect non-existent packages (40+ patterns)	✅ Done
🎭 Hallucinated Methods	Detect JS patterns like .push(), .length	✅ Done
📦 Unused Imports	AST-based detection	✅ Done
💀 Dead Code	Unused functions/classes	✅ Done
🔄 Duplicate Detection	Cross-file copy-paste	✅ Done
🎨 Rich Output	Colors and tables (optional)	✅ Done
⚙️ Config Support	pyproject.toml configuration	✅ Done

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📦 Installation

# Install from GitHub
pip install git+https://github.com/rsionnach/sloppy.git

# With colored output (recommended)
pip install "sloppylint[rich] @ git+https://github.com/rsionnach/sloppy.git"

# With all optional features
pip install "sloppylint[all] @ git+https://github.com/rsionnach/sloppy.git"

# Or clone and install for development
git clone https://github.com/rsionnach/sloppy.git
cd sloppy
pip install -e ".[dev]"

# Verify
sloppy --version

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⚙️ Configuration

Configure via pyproject.toml:

[tool.sloppy]
ignore = ["tests/*", "migrations/*"]
disable = ["magic_number", "debug_print"]
severity = "medium"
max-score = 100
ci = false
format = "detailed"  # or "compact" or "json"

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🤝 Contributing

git clone https://github.com/rsionnach/sloppy.git
cd sloppy
pip install -e ".[dev]"
pytest tests/ -v  # 57 tests should pass

See AGENTS.md for coding conventions and pattern implementation guide.

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📄 License

MIT

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🙏 Acknowledgments

Inspiration

• KarpeSlop - The original AI Slop Linter for TypeScript
• Andrej Karpathy's commentary on AI-generated code quality

Research

• Counterfeit Code - MIT research on "looks right but doesn't work" patterns
• Package Hallucinations - USENIX study on hallucinated dependencies