Slop Eval MCP server

<!-- mcp-name: io.github.RudrenduPaul/slop-eval-cli -->

slop-eval

Quickstart • CLI reference • Library API • MCP Server • Comparison • FAQ

Score AI-generated UI for genericness with an LLM judge, so a CI check catches the same "this looks like every other AI-built app" problem a human reviewer would flag on sight.

npx slop-eval-cli score --screenshot ./preview.png --json

No install step: npx fetches and runs the published npm package directly. Prefer Python? pip install slop-eval-cli gets you the same CLI as a genuine, independent port of the scoring logic.

Two distributions: npm and Python, both live

slop-eval-cli is live on both npm and PyPI (package slop_eval). The Python port is a genuine, independent implementation, built and tested (60/60 tests, verified in this pass) against the same rubric and Anthropic judge prompt as the TypeScript original. See python/README.md for Python-specific usage.

Why this exists, and what it isn't

Nutlope's Hallmark, a popular AI design skill with 21,000+ stars, has an open issue where a user says flatly: "all of it looks like slop." The maintainer closed it NOT_PLANNED. Separately, a contributor opened a PR against Hallmark titled "Add eval-driven quality harness for Hallmark outputs" that has sat open and unmerged for about two months as of this writing. Both are real and dated as of this writing. Neither proves the demand is large, only that the gap is real and currently unaddressed.

slop-eval is not the first tool in this space, and it doesn't try to be. Two real, free tools already sit nearby:

• Impeccable (pbakaus/impeccable, 54,000+ stars, Apache 2.0) ships a CLI that flags 59 specific visual tells of AI-generated UI (gradient palettes, glassmorphism, side-stripe borders, WCAG contrast violations), all enabled by default with no model call; a separate impeccable critique command adds further, opt-in LLM-based judgments on top. Core detection stays fast because it doesn't need a model for any of its default checks. It has grown well beyond a slop detector into a full design-language skill for Claude Code, Cursor, and Codex, with 23 commands total.
• aislop (MIT, 500+ stars) does the deterministic, rule-based equivalent for AI-generated code (not UI): 50+ regex/AST rules across 8 languages, no LLM in the runtime path, positioned exactly as a CI quality gate.

Neither does holistic, judgment-based UI scoring: "does this layout feel novel," "does this component choice feel considered," the kind of read a fixed rule can't easily encode. That's the gap slop-eval fills, built to compose with tools like Impeccable's rather than replace them.

Features

Verified directly against the code in this repo:

Shortened. The full README is on GitHub.