com.sloppatterns/slop-patterns

Slop Patterns

Checks UI code for AI-default design patterns and gives the fix. By Precious Studio.

Endpointhttps://sloppatterns.com/mcp (streamable-http)
Registry version1.2.1
Now7 tools · grade A (94) · pin ts_1edf3c079d07f471547df7c7eff3fcb9 · protocol 2025-06-18
First / last listed2026-10-27 07:58 UTC / 2026-10-27 07:58 UTC
Grade over time2026-10-27: A (94), 7 tools

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Timeline

First listing · 2026-10-27 07:58 UTC
7 tools, grade A (94)

Tools: check_design list_patterns get_pattern changelog search_patterns report_pattern why

Current tools (7)

check_designCheck a snippet of CSS, HTML or JSX against the Slop Patterns library and return every AI design anti-pattern it matches, with the fix for each. Covers the 101 documented patterns that have a mechanical tell. Useful for reviewing generated UI code.
params: code*, shareStats
list_patternsList the whole Slop Patterns taxonomy: code, id, name and one-liner for every documented AI design anti-pattern.
params: track
get_patternGet one full pattern entry by id or code (e.g. "a1" or "the-unchosen-gradient"): what it looks like, why the tools produce it, who it hurts, the fix, sources.
params: id*
changelogThe library version, what each release added or changed, and how patterns are versioned. Use it to cite a specific version of Slop Patterns.
params: none
search_patternsPlain-language search across the library. "gradient headline" returns A10 Gradient Text Headline.
params: query*
report_patternReport an AI design anti-pattern that is NOT yet in the library, for a design failure seen repeatedly that a search of the library does not find. Reports are reviewed by a human before anything is published, and published entries credit the reporter.
params: name*, description*, whereSeen, example, credit
whyReturn only the causal explanation for one pattern — which model, tool or template default produces it.
params: id*

Entries describe changes in tool definitions. They are not statements about a server, its quality or its author. The grade measures how the tool definitions fit model providers (token cost, schema compatibility, confusable names) as scored by the ToolFit engine at the time of the listing. JSON: append .json. Opt-out: how or hello@youraitools.co.