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FixMySlop

PyPI npm CI License: MIT

The slop linter for the AI-agent era. FixMySlop catches the things AI coding agents get wrong — the purple-gradient landing page, the // ... existing code ... that silently deleted half a file, the npm package that doesn't exist, the OpenAI key in NEXT_PUBLIC_ — in milliseconds, without an LLM. Then it hands a precise fix list to the agent you already use (Claude Code, Codex, Cursor, Gemini) and re-scans to prove it's fixed.

fixmyslop scan output: 31 issues across UI slop, accessibility, code slop, security and dependencies, slop score 100, grade F

Why this exists when you already have a frontier model

Frontier models are great at fixing slop and bad at noticing their own. They write the purple gradient because it's the statistical default; they elide code when an edit gets long; they import packages that sound right. FixMySlop is the other half of the loop:

Your agent FixMySlop
Speed seconds–minutes per review ~0.5s for a 10k-line repo
Determinism different answer each run same input → same findings, stable rule IDs
Cost tokens on every review free, offline, no API key
Good at fixing code finding the tells, every time, in CI

So: FixMySlop finds, your agent fixes, FixMySlop verifies. The old "local LLM reviews your code" mode still exists (--llm), but it's optional — the rules engine is the product.

Install

pipx install fixmyslop            # or: pip install fixmyslop
npx fixmyslop scan                # JavaScript projects: no install step (runs via uvx/pipx)

npx needs Python 3.10+ plus uv or pipx on the machine; it always runs the FixMySlop version that matches the npm package.

Optional: pip install "fixmyslop[analysis]" adds Ruff + Bandit findings for Python.

30 seconds

fixmyslop scan                    # whole repo
fixmyslop scan --changed          # only what changed vs main (+ uncommitted)
fixmyslop baseline                # existing codebase: accept today's issues, report only new ones
fixmyslop ui                      # the app: browse issues, apply fixes, copy prompts for your agent
fixmyslop scan --open             # one-off interactive HTML report
fixmyslop fix --safe-only         # behavior-preserving auto-fixes
fixmyslop fix                     # safe fixes → hand the rest to your agent → re-scan
fixmyslop init --claude           # make Claude Code check its own work, live

Try it on the bundled demos: fixmyslop ui examples/slop-app (classic purple-gradient slop) and fixmyslop scan examples/slop-2026 (the newer dark, glowing, aphorism-heavy look).

For AI agents

If a user asks you to set up or run FixMySlop, these are the exact commands (all exist in the CLI; fixmyslop <command> --help shows every option):

pip install fixmyslop                  # needs internet access to PyPI (sandboxes without network can't install it)
fixmyslop init --all                   # config + agent rules + skill + MCP + Claude hook + CI + pre-commit
fixmyslop scan . -f compact            # one line per issue, token-efficient
fixmyslop scan . -f prompt             # full fix brief: issues, exact fixes, the project's design tokens
fixmyslop fix . --safe-only            # behavior-preserving auto-fixes only
fixmyslop scan . --fail-on medium      # exit 1 while CRITICAL/HIGH/MEDIUM issues remain
fixmyslop rules <rule-id>              # why a rule exists and how to fix it

Loop: scan → fix what the brief says → re-scan until clean. Report the before/after slop score to the user. Supported files: Python, JS/TS, JSX/TSX, Vue, Svelte, Astro, HTML, CSS/SCSS (plus generic checks for Go, Rust, Java, C/C++, C#, Ruby, PHP, Swift, Kotlin).

The app

fixmyslop ui opens FixMySlop in your browser. It runs only on your machine (127.0.0.1, per-session token, no external requests) and uses the same engine as the CLI:

  • Overview: slop score with the change since your last scan, what to fix first, and three steps to fix it
  • Issues: filter and search every finding, see the exact code, and copy a fix prompt for your agent
  • Rules: turn rules on or off for the project (saved to .fixmyslop.yml)
  • Setup: one-click install for Claude Code, Cursor, AGENTS.md, GitHub Actions and pre-commit
FixMySlop app overview: slop score 100, grade F, three fix steps, issues by category and the most affected files FixMySlop issues view: findings grouped by file, with the explanation, highlighted code and the exact fix for the selected issue

What it catches

UI slop — the visual and copy tells of generated frontends (React, Vue, Svelte, Astro, HTML, CSS, Tailwind)

Rule Catches
ui/ai-gradient from-purple-600 to-pink-500, #667eea → #764ba2
ui/gradient-text bg-clip-text text-transparent headlines
ui/emoji-icons 🚀 ⚡ ✨ used as feature icons
ui/marketing-slop "Revolutionize", "Unlock the power of", "seamless", "next-gen"
ui/fake-social-proof "10,000+ happy users", "99.9% uptime", testimonials from "Sarah Johnson"
ui/placeholder-copy Lorem ipsum, "Your Company Name"
ui/glassmorphism, ui/blur-blobs, ui/hover-scale, ui/heavy-shadows, ui/gimmick-animation the template aesthetic
ui/rainbow-palette, ui/palette-sprawl, ui/arbitrary-color, ui/arbitrary-values no design system: 9 accent hues, 40 hex codes, w-[347px]
ui/default-font, ui/z-index-war, ui/important-abuse Inter-everywhere, z-index: 9999, !important piles
ui/aphorism-copy the newer AI voice: "Make space for what matters", "Intentional by design", "Less X. More Y."
ui/neon-glow, ui/two-tone-headline, ui/eyebrow-labels glowing orbs in any hue, accent-colored second line, uppercase micro-labels on every section
ui/fake-chart sparklines drawn from hard-coded heights, often right next to a "0"

Accessibility — a11y/img-alt, a11y/clickable-div, a11y/icon-button, a11y/focus-removed, a11y/dead-link

Code slop — slop/elided-code (// ... existing code ...), slop/placeholder-impl ("in a real app you would…"), slop/stub-function, slop/swallowed-exception, slop/empty-catch, slop/bare-except, slop/narrating-comment, slop/step-comments, slop/debugger, slop/console-log, slop/emoji-log, slop/ts-any, slop/ts-ignore, slop/blanket-suppression, slop/placeholder-credential, slop/ai-voice

Backend — slop/empty-test (tests that assert nothing — pytest, Jest, Vitest, Mocha), slop/duplicate-function (the same body copy-pasted across files, names ignored), slop/pointless-wrapper, slop/catch-rethrow, Go slop/ignored-error (if err != nil { return nil }), Java/Kotlin slop/print-stacktrace, and empty catch {} in JS/TS, Java, C#, Kotlin, Swift, PHP and Dart

Dependencies — deps/phantom-import: imports that aren't stdlib, local, declared, or installed (hallucinated packages are what slopsquatting attacks register). --online confirms against PyPI / npm. deps/undeclared-import: works on your machine, breaks in CI.

Security — sec/leaked-key (OpenAI/Anthropic/AWS/GitHub/Stripe/Google key formats, private keys — always redacted in output), sec/public-env-secret (NEXT_PUBLIC_*SECRET*, VITE_*OPENAI*), sec/hardcoded-credential, sec/sql-injection, sec/cors-wildcard, sec/tls-disabled, sec/raw-html, sec/eval

Plus Ruff, Bandit and Semgrep findings when installed. fixmyslop rules lists everything; fixmyslop rules ui/ai-gradient explains one.

Use it with your agent

Claude Code

fixmyslop init --claude

This installs four things, all idempotent:

  • a skill (.claude/skills/fixmyslop/SKILL.md) so Claude reaches for FixMySlop on its own when it builds UI or finishes a task
  • an MCP server in .mcp.json with check_slop, fix_safe, explain_rule, slop_guide tools
  • a PostToolUse hook — every file Claude writes is checked instantly; only the lines it just wrote are reported, and Claude is told to fix them before moving on
  • anti-slop rules in CLAUDE.md

fixmyslop init --user installs the skill for every project on your machine.

Cursor, Codex, Gemini, Windsurf, anything with MCP

fixmyslop init --cursor          # .cursor/rules + .cursor/mcp.json
fixmyslop init --agents          # AGENTS.md (Codex, Gemini, Jules, Copilot agents)
claude mcp add fixmyslop -- fixmyslop mcp     # or register the MCP server anywhere

MCP config for JSON-configured clients (Cursor, Windsurf, Claude Desktop):

{ "mcpServers": { "fixmyslop": { "command": "npx", "args": ["-y", "fixmyslop", "mcp"] } } }

Hand off a fix

fixmyslop fix                          # auto-detects claude / codex / gemini on PATH
fixmyslop fix --agent claude --yes
fixmyslop fix --agent-cmd "aider --message-file {brief} --yes"
fixmyslop fix --agent llm -b https://openrouter.ai/api/v1 -m <model>   # any OpenAI-compatible API, incl. Ollama
fixmyslop scan -f prompt > brief.md    # or paste the brief yourself

fix applies safe deterministic fixes first, writes a brief to .fixmyslop/brief.md (file-by-file checklist with a concrete fix for every rule plus UI design direction), runs the agent, re-scans, and repeats for up to --rounds. It ends with the before/after score.

Existing codebase? Baseline it

fixmyslop baseline          # accept today's issues (writes .fixmyslop-baseline.json — commit it)
fixmyslop scan --fail-on high   # from now on only NEW slop is reported and fails CI
fixmyslop scan --no-baseline    # see everything again

Fingerprints ignore line numbers, so editing code above an old issue doesn't bring it back. Also available in the app under Setup.

CI

# .github/workflows/fixmyslop.yml   (or: fixmyslop init --github)
on: [pull_request]
permissions: { contents: read, security-events: write }
jobs:
  slop:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
        with: { fetch-depth: 0 }
      - uses: MrSpideyNihal/FixMySlop@v0.6.0
        with: { fail-on: high, changed-only: true }

Findings show up as inline PR annotations (SARIF). Also on the GitHub Marketplace. pre-commit:

repos:
  - repo: https://github.com/MrSpideyNihal/FixMySlop
    rev: v0.6.0
    hooks: [{ id: fixmyslop }]

Configure

.fixmyslop.yml (or [tool.fixmyslop] in pyproject.toml), created by fixmyslop init:

exclude: ["legacy/**", "**/*.generated.ts"]
disable: ["ui/default-font"]           # ids or groups: ui, a11y, slop, sec, deps
severity: {"slop/console-log": "INFO"}
fail_on: high
hook: { min_severity: MEDIUM }

Silence one finding with a reason: // fixmyslop-ignore[ui/gradient-text] brand guideline. Skip a file: fixmyslop-ignore-file in its first lines. Paths passed explicitly are always scanned.

Output formats

-f text (default) · compact (one line per issue, for agents) · prompt (fix brief) · sarif · json · markdown · html (a shareable single file with filters, search and "copy fix prompt" per file) · csv · pdf. Save with -s report.html (format inferred from the extension). Exit codes: 0 clean, 1 issues at/above --fail-on, 2 usage error.

How accurate is it?

On a pinned corpus of 9 AI-built apps and 4 hand-built repos, 95% of findings were correct in a random, hand-reviewed sample of 80, and AI-built apps averaged about 2× more findings per 1,000 lines. Method, raw labels, per-repo grades and limitations: benchmarks/BENCHMARK.md. Reproduce with python benchmarks/run.py.

Slop score

0 (clean) to 100, from severity-weighted findings per 1,000 lines, so a 500-line app and a 500k-line monorepo are comparable. Grades: A < 10 ≤ B < 25 ≤ C < 45 ≤ D < 65 ≤ F. FixMySlop's own repo is scanned in CI and holds an A.

Optional: LLM review

fixmyslop scan --llm adds a model review pass over each file (Ollama, llama.cpp, vLLM, LM Studio, or any OpenAI-compatible endpoint via --base-url/--api-key/--model, or FIXMYSLOP_* env vars). It's slow and non-deterministic, so it's off by default — every check above works without it.

Development

pip install -e ".[analysis,dev]"
pytest -q
fixmyslop scan . --fail-on medium     # the repo must stay clean
python screenshots/make_screenshots.py   # regenerate README screenshots

Adding a rule: write a check in fixmyslop/core/slop/rules_*.py with the @rule decorator (or line_rule for a regex), then add a sloppy + clean pair to tests/test_slop_rules.py. Every rule needs a why and an actionable fix — the fix text is what agents follow.

Security and changes

See SECURITY.md for how FixMySlop handles your code (local, offline by default, secrets redacted) and how to report a vulnerability, and CHANGELOG.md for what changed in each release.

License

MIT

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