Anti-slop frontend skill for landing pages, portfolios, and redesigns. The agent reads the brief, infers the right design direction, and ships interfaces that do not look templated. Real design systems when applicable, audit-first on redesigns, strict pre-flight check.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# tasteskill: Anti-Slop Frontend Skill
> Landing pages, portfolios, and redesigns. Not dashboards, not data tables, not multi-step product UI.
> Every rule below is **contextual**. None of it fires automatically. First read the brief, then pull only what fits.
---
## 0. BRIEF INFERENCE (Read the Room Before Anything Else)
Before touching code or tweaking dials, **infer what the user actually wants**. Most LLM design output is bad because the model jumps to a default aesthetic instead of reading the room.
### 0.A Read these signals first
1. **Page kind** - landing (SaaS / consumer / agency / event), portfolio (dev / designer / creative studio), redesign (preserve vs overhaul), editorial / blog.
2. **Vibe words** the user used - "minimalist", "calm", "Linear-style", "Awwwards", "brutalist", "premium consumer", "Apple-y", "playful", "serious B2B", "editorial", "agency-y", "glassy", "dark tech".
3. **Reference signals** - URLs they linked, screenshots they pasted, products they named, brands they're competing with.
4. **Audience** - B2B procurement panel vs. design-conscious consumer vs. recruiter scanning a portfolio. The audience picks the aesthetic, not your taste.
…
The line at the top of this page pins the label git:20260912.4b461b8, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
B 16 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
fail: No script tag (matched: <script)
pass: Frontmatter block present
pass: Frontmatter declares a name
pass: Frontmatter declares a description
pass: Size between 200 bytes and 200 KB (88459 bytes)
pass: No zero-width or bidi control characters
pass: No instruction hidden inside an HTML comment
pass: No link to an exfiltration or paste host
pass: No credential-shaped string
pass: No instruction to send local credentials anywhere
pass: No text hidden with inline styles
pass: No prompt-injection phrasing
pass: No curl or wget piped into a shell
pass: No recursive delete of root, home or parent
pass: No instruction to read or print local credentials
pass: No base64 blob over 200 characters
pass: No link to a raw IP address
Starting a new one? Use a template for SKILL.md on mdpantry, which passes every one of these checks and says what to change in it.
Source
GitHub
xu123-bob/baize · 590 stars · license MIT · pushed 2026-10-31 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_46k4fxj4h2kytcdt
GET https://markdownregistry.com/api/v1/resolve?ref=xu123-bob/baize/design-taste-frontend
GET https://markdownregistry.com/api/v1/blob/2e064e92aca020b2e0bad69326fe7ea55d59005ed53d1a8cbce1bd135d44b8b3
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
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