Creator · BlackBeltTechnology
Last updated · Sep 3, 2026
A mechanical, countable anti-slop checklist for AI-generated frontend. Catches the specific signatures an undirected model defaults to: AI-purple glows, Inter-everywhere, em-dashes, div-based fake screenshots, eyebrow-on-every-section, beige+brass \"premium\" palettes, generic Ja
Creator · BlackBeltTechnology
Last updated · Sep 3, 2026
A mechanical, countable anti-slop checklist for AI-generated frontend. Catches the specific signatures an undirected model defaults to: AI-purple glows, Inter-everywhere, em-dashes, div-based fake screenshots, eyebrow-on-every-section, beige+brass \"premium\" palettes, generic Ja
Creator · BlackBeltTechnology
Last updated · Sep 3, 2026
A mechanical, countable anti-slop checklist for AI-generated frontend. Catches the specific signatures an undirected model defaults to: AI-purple glows, Inter-everywhere, em-dashes, div-based fake screenshots, eyebrow-on-every-section, beige+brass \"premium\" palettes, generic Ja
Creator · BlackBeltTechnology
Last updated · Sep 3, 2026
A mechanical, countable anti-slop checklist for AI-generated frontend. Catches the specific signatures an undirected model defaults to: AI-purple glows, Inter-everywhere, em-dashes, div-based fake screenshots, eyebrow-on-every-section, beige+brass \"premium\" palettes, generic Ja
Sandbox only
Install targets
Codex install prompt
Install the "anti-slop-frontend" agent skill from https://github.com/BlackBeltTechnology/pi-agent-dashboard/tree/develop/packages/anti-slop/.pi/skills/anti-slop-frontend. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: A mechanical, countable anti-slop checklist for AI-generated frontend. Catches the specific signatures an undirected model defaults to: AI-purple glows, Inter-everywhere, em-dashes, div-based fake screenshots, eyebrow-on-every-section, beige+brass \"premium\" palettes, generic Jane Doe / Acme data. Advisory layer that pairs with frontend-mockup-loop (which owns the cite-a-source loop plus WCAG gates) but works standalone in any React/Tailwind/HTML project. Triggers: \"does this look AI-generated\", \"anti-slop pass\", \"remove the AI tells\", \"why does this look templated\", \"design review for slop\". After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"blackbelttechnology-anti-slop-frontend","task":"Install anti-slop-frontend","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add BlackBeltTechnology/pi-agent-dashboard --skill anti-slop-frontend
Maintenance
fresh
2d since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
270
71/100 Quality · 77/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · Financial research output is not financial advice; require human review before any live investment decision.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
270 GitHub stars
Repo activity
270 stars, 38 forks
Maintenance
2d since push
License
MIT
Install
npx skills add BlackBeltTechnology/pi-agent-dashboard --skill anti-slop-frontend
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add BlackBeltTechnology/pi-agent-dashboard --skill anti-slop-frontendDo not use when
Alternative
1.9K Stars
npx skills add yanliudesign/mono-color-skill --skill mono-color
Alternative
61.0K Stars
npx skills add mvanhorn/last30days-skill -g
Alternative
38.4K Stars
npx skills add Imbad0202/academic-research-skills
Alternative
28.0K Stars
npx skills add assafelovic/gpt-researcher
Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill may drive a browser or interact with web pages.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20anti-slop-frontend%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20anti-slop-frontend%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/blackbelttechnology-anti-slop-frontend/install
Agent should check
Copy prompt
Task: Use anti-slop-frontend in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20anti-slop-frontend%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/blackbelttechnology-anti-slop-frontend/install
Install command: npx skills add BlackBeltTechnology/pi-agent-dashboard --skill anti-slop-frontend
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/blackbelttechnology-anti-slop-frontend/install
LLM text format
/api/skills/blackbelttechnology-anti-slop-frontend/install?format=text
Find alternatives
/api/skills/search?q=anti-slop-frontend&limit=3
Agent prompt
Use anti-slop-frontend for this task. Review https://www.openagentskill.com/api/skills/blackbelttechnology-anti-slop-frontend/install, then install with: npx skills add BlackBeltTechnology/pi-agent-dashboard --skill anti-slop-frontendRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/blackbelttechnology-anti-slop-frontend
LLM text
/api/registry/manifest/blackbelttechnology-anti-slop-frontend?format=text
Install alias
/api/registry/install/blackbelttechnology-anti-slop-frontend
Recommend
/api/registry/recommend?task=Use%20anti-slop-frontend%20in%20an%20agent%20workflow&limit=3
Agent fit
Local desktop
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Local desktop
Trust label
Prototype first
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO270 GitHub stars
Stars/forks activity
CHECK270 stars, 38 forks; issue activity unavailable in current metadata
Recent maintenance
PASS2d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Workflow fit
Design, build, test, and ship interfaces
A practical workflow for agents that turn product briefs or Figma designs into polished frontend code, review the result, test it in a browser, and prepare a safe deployment.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Alternative shortlist
Similar skills that may fit this task.
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills for Claude Code: research → write → review → revise → finalize
Run autonomous deep research over web and local sources
--- name: anti-slop-frontend description: "A mechanical, countable anti-slop checklist for AI-generated frontend. Catches the specific signatures an undirected model defaults to: AI-purple glows, Inter-everywhere, em-dashes, div-based fake screenshots, eyebrow-on-every-section, beige+brass \"premium\" palettes, generic Jane Doe / Acme data. Advisory layer that pairs with frontend-mockup-loop (which owns the cite-a-source loop plus WCAG gates) but works standalone in any React/Tailwind/HTML project. Triggers: \"does this look AI-generated\", \"anti-slop pass\", \"remove the AI tells\", \"why does this look templated\", \"design review for slop\"." license: MIT metadata: author: blackbelt-technology version: "0.1" adapted_from: "Leonxlnx/taste-skill (design-taste-frontend, MIT) - countable rules distilled, stack-coupling removed, scoped universal vs marketing-only." ---
# anti-slop-frontend
A flat, **mechanical** checklist of the concrete signatures an undirected model emits when it tries to "look designed." Every rule here is **countable or binary** - you can mechanically verify pass/fail, not argue taste. That is the whole point: "it looks better" is not a check; "eyebrow count > ceil(sections/3)" is.
## What this is, and is NOT
- **IS** an advisory catalog of AI-tells, scoped by surface kind. - **IS** standalone - works with no tooling, in any React/Tailwind/HTML project. - **IS NOT** a design philosophy, a loop, or a gate. It scores; it never blocks.
### Relationship to `frontend-mockup-loop`
Different jobs, intentionally separate:
| | frontend-mockup-loop | anti-slop-frontend (this) | |---|---|---| | Shape | ground→contract→mockup→test→fix→learn **loop** | flat **checklist** | | Basis | cite an **external public rule** (Nielsen, WCAG, Laws of UX) | codified **AI-tell catalog** | | Authority | owns the **hard gates** (WCAG-AA, severity-4) | **advisory only**, drives the fix list | | Domain | product UI, dashboards, flows | universal tells + marketing-surface tells |
When both are present: the loop's a11y floor and cite-a-source rule **win**. This skill feeds concrete failing items into the loop's FIX step. It never overrides a gate, and a tell here is never a reason to violate a cited rule.
> **Honesty note:** these rules are curated *taste*, hardened into countable > form. They are good defaults, not laws of nature. Every rule has an **override > path**: when the brief explicitly asks for the "banned" thing, it is allowed - > execute it with intent, not by accident.
---
## The three dials (set once, up front)
State these before reviewing or generating. They gate which rules fire and how hard.
- **`VARIANCE` (1-10)** - 1 = perfect symmetry, 10 = artsy chaos - **`MOTION` (1-10)** - 1 = static, 10 = cinematic/physics - **`DENSITY` (1-10)** - 1 = art-gallery airy, 10 = cockpit/packed-data
Infer from the brief; don't silently use a baseline. Dashboards/data UI live high on DENSITY and low on VARIANCE/MOTION. Landing/portfolio live the opposite.
---
## PART A - Universal tells (apply to EVERY surface, dashboards included)
These fire regardless of surface kind. A dense admin panel is just as guilty of AI-purple and Inter-everywhere as a landing page.
### A1. Color - **No AI-purple/blue glow as default.** No automatic violet button glows, no random neon gradients ("the Lila tell"). Neutral base (Zinc/Slate/Stone) + ONE high-contrast accent. *Override:* brand literally is purple. - **Max 1 accent color, saturation < 80% default.** Lock it: the same accent on the whole page. A warm-grey UI does not grow a blue CTA in section 7. - **One neutral temperature per project.** Don't drift warm-grey ↔ cool-grey. - **No pure `#000000` / pure `#ffffff`.** Off-black (zinc-950) and off-white; pure values kill depth.
### A2. Typography - **Inter is discouraged as the *default*.** Reach past it (Geist, Outfit, Cabinet Grotesk, Satoshi) unless the brief wants neutral/Linear-style or is accessibility-first. *Override exists.* - **Serif is very discouraged as default.** "Feels premium/creative" is not a reason. Specifically banned as defaults: **Fraunces, Instrument Serif**. Serif only when the brief names one or the family is genuinely editorial/luxury/heritage. - **Emphasis = italic/bold of the SAME family.** Never inject a random serif word into a sans headline for "visual interest." - **One corner-radius scale per page** (all-sharp / all-soft / all-pill), or a documented rule followed everywhere.
### A3. The em-dash ban (the #1 tell) - **Zero `—` and zero `–`-as-separator anywhere visible.** Headlines, labels, pills, body, quotes, attribution, captions, buttons, alt text. No "sparingly." Replace with a period, comma, colon, parentheses, line break, or a spaced hyphen ` - `. Ranges use a plain hyphen (`2018-2026`, `€40-80k`). - Mechanical check: grep the rendered output for `—`/`–`. Any hit = fail.
### A4. Fake data ("Jane Doe" effect) - **No generic names.** "John Doe / Sarah Chan / Jack Su" → realistic, locale-appropriate names. - **No generic brand names.** "Acme / Nexus / SmartFlow / Cloudly" → contextual names that sound real. - **No fake-perfect numbers.** `99.99%`, `50%`, `1234567` → organic values (`47.2%`, real-looking phone formats). Fake-precise engineering specs (`5.8mm`, `4.1×`) are banned unless from real data or labeled mock. - **No filler verbs.** "Elevate / Seamless / Unleash / Next-Gen / Revolutionize" → concrete verbs. - **No generic avatars** (SVG "egg", default user glyph) → believable placeholders.
### A5. Assets & icons - **No div-based fake screenshots.** Building a fake dashboard/terminal/task-list out of styled `<div>`s is the single biggest tell. Use a real screenshot, a generated image, a real mini component preview, or nothing. - **No hand-rolled SVG icons.** Use one icon family (Phosphor / HugeIcons / Radix / Tabler), standardized stroke width. Lucide only on explicit request. - **No hand-rolled decorative SVG illustrations** as default. - **No broken image links.** Use `picsum.photos/seed/{descriptive}/{w}/{h}` or generated assets, never dead Unsplash URLs.
### A6. Interactive states (the "happy-path only" tell) - **Loading / empty / error states exist**, not just the static success state. Skeletons match final layout shape; avoid generic spinners. - **Button contrast (a11y).** Every CTA's text passes WCAG AA against its own background. No white-on-white, no transparent button on same-color bg with no border. *(This one is also a hard gate when frontend-mockup-loop runs.)* - **Form contrast (a11y).** Inputs, placeholders, focus rings, helper, error text all pass AA against the section bg. Label above input; never placeholder-as-label.
### A7. Motion must be motivated - **Every animation justifies itself in one sentence** - hierarchy, storytelling, feedback, or state-transition. "It looked cool" is not valid. Motion-for-show is amateur. - **Motion claimed = motion shown.** If `MOTION > 4`, the page actually moves; if you can't ship working motion, drop the dial and ship clean static. - **Banned mechanism: `window.addEventListener('scroll', …)`** and React-state scroll/rAF loops. Use scroll-driven CSS, IntersectionObserver, or a motion library's scroll primitives. - **Reduced-motion honored** for anything above `MOTION 3`.
---
## PART B - Marketing-surface tells (landing / portfolio / about ONLY)
Skip Part B entirely for dashboards, data tables, wizards, editors, product UI. These rules govern hero-driven marketing pages, where the model's worst templating habits live.
### B1. Hero discipline - **Hero fits the initial viewport.** Headline ≤ 2 lines, subtext ≤ 20 words and ≤ 4 lines, CTA visible without scroll. A 4-line headline is a font-size error. - **Hero top padding ≤ `pt-24` desktop** (content must not float mid-viewport). - **Max 4 text elements in the hero**: (eyebrow OR brand strip), headline, subtext, CTAs. Banned in hero: trust micro-strip, pricing teaser, tagline under CTAs, feature bullets, avatar row - those move to sections below. - **No version labels** (`V0.6`, `BETA`, `INVITE-ONLY`) unless the brief is a launch.
### B2. The eyebrow tell (#1 violated rule) - An "eyebrow" = small uppercase wide-tracking label above a section headline (`text-[11px] uppercase tracking-[0.18em]`). - **Max 1 eyebrow per 3 sections** (hero counts as 1). Mechanical check: count `uppercase tracking` micro-labels above headlines; fail if > ceil(sections/3). - **No section-number eyebrows** (`00 / INDEX`, `001 · Capabilities`, `06 · how it works`). The section's position already categorizes it. - **Default fix: drop the eyebrow.** The headline alone is enough.
### B3. Layout repetition - **No 3 equal feature cards.** The "three identical horizontal cards" row is the default. Use asymmetric grid, zig-zag, or a different family. - **Zigzag cap: max 2 consecutive image+text splits.** The 3rd in a row is a fail. - **Section-layout-repetition ban.** A layout family appears at most once. 8 sections → ≥ 4 distinct families. - **No split-header** ("big left headline + small right floating paragraph") as default. Stack headline over body instead. - **Bento: exact cell count, real rhythm, background diversity.** N items → N cells (no empty tiles); ≥ 2-3 cells have real visual variation (image, gradient, pattern), not all white-on-white text cards. - **Marquee: max one per page.**
### B4. CTA & social proof - **No duplicate CTA intent.** "Get in touch" + "Let's talk" + "Contact us" on one page = fail. One label per intent, everywhere. - **No CTA wraps to 2+ lines at desktop** (shorten label or widen button). - **Logo wall lives UNDER the hero, is logos only** (no industry labels beneath), uses real SVG marks (Simple Icons / devicon) or generated monograms, not plain text wordmarks.
### B5. Decoration tells (banned by default) - **No decoration text strip** at hero bottom (`BRAND. MOTION. SPATIAL.`). - **No locale / city / time / weather strips** (`LIS 14:23 · 18°C`) unless the brief is genuinely place- or timezone-focused. - **No scroll cues** (`Scroll`, `↓ scroll`, `Scroll to explore`). - **No version footers** (`v1.4.2`, `Build 0048`, `last sync 4s ago`) on marketing pages - those are devtool fixtures. - **The middle-dot `·` is rationed** (max 1 per metadata line; not the default separator for everything). - **No decorative status dots** before every nav item / row / badge. Only for real semantic state, sparingly. - **No pills/labels overlaid on images** and **no pretentious photo-credit captions** (`Field study no. 12 · Ines Caetano`) on stock/placeholder images. - **No poetic section labels** ("From the field", "Field notes", "On our desks") → plain functional labels or none. - **No `border-t` + `border-b` on every row** of a long list/spec table. Long lists (>5 items) use a real component (grouped chunks, card grid, tabs, scroll-snap), not a hairline-per-row `<ul>`.
### B6. Copy self-audit - Re-read every visible string. Flag and rewrite: grammatically broken phrases, unclear referents, cute-but-wrong wordplay, fake-craftsman micro-meta. Plain functional copy beats AI-cute copy.
---
## Mechanical pre-flight (the grep-able subset)
The rules below can be checked by string-search, not judgment. Run them last.
- [ ] **Em-dash:** zero `—` / `–`-as-separator in rendered output (A3). - [ ] **AI-purple:** no default violet glow/gradient unless brand-justified (A1). - [ ] **Accent lock:** one accent hex family across all sections (A1). - [ ] **Default font:** not Inter (unless justified); serif is not Fraunces / Instrument Serif (A2). - [ ] **Fake data:** no "Doe / Acme / 99.99% / Elevate" (A4). - [ ] **Fake screenshots:** no div-built product UI; no hand-rolled icon paths (A5). - [ ] **CTA/form contrast:** every CTA + input passes WCAG AA (A6). - [ ] **Motion:** no `addEventListener('scroll')`; reduced-motion present (A7). - [ ]
Source provenance
Decision snapshot
recent repository activity
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for anti-slop-frontend, ready for a manual X post.
anti-slop-frontend: A mechanical, countable anti-slop checklist for AI-generated frontend. Catches the specific s... 270 stars https://www.openagentskill.com/skills/blackbelttechnology-anti-slop-frontend?ref=x
Listing + install path for anti-slop-frontend: https://www.openagentskill.com/skills/blackbelttechnology-anti-slop-frontend?ref=x Install: npx skills add BlackBeltTechnology/pi-agent-dashboard --skill anti-slop-frontend
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[](https://www.openagentskill.com/skills/blackbelttechnology-anti-slop-frontend?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)BlackBeltTechnology
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Sandbox only
mono-color
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
1.9K StarsLast30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
61.0K StarsAcademic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
38.4K StarsGPT Researcher
Run autonomous deep research over web and local sources
28.0K StarsSandbox only
Install targets
Codex install prompt
Install the "anti-slop-frontend" agent skill from https://github.com/BlackBeltTechnology/pi-agent-dashboard/tree/develop/packages/anti-slop/.pi/skills/anti-slop-frontend. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: A mechanical, countable anti-slop checklist for AI-generated frontend. Catches the specific signatures an undirected model defaults to: AI-purple glows, Inter-everywhere, em-dashes, div-based fake screenshots, eyebrow-on-every-section, beige+brass \"premium\" palettes, generic Jane Doe / Acme data. Advisory layer that pairs with frontend-mockup-loop (which owns the cite-a-source loop plus WCAG gates) but works standalone in any React/Tailwind/HTML project. Triggers: \"does this look AI-generated\", \"anti-slop pass\", \"remove the AI tells\", \"why does this look templated\", \"design review for slop\". After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"blackbelttechnology-anti-slop-frontend","task":"Install anti-slop-frontend","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add BlackBeltTechnology/pi-agent-dashboard --skill anti-slop-frontend
Maintenance
fresh
2d since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
270
71/100 Quality · 77/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · Financial research output is not financial advice; require human review before any live investment decision.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
270 GitHub stars
Repo activity
270 stars, 38 forks
Maintenance
2d since push
License
MIT
Install
npx skills add BlackBeltTechnology/pi-agent-dashboard --skill anti-slop-frontend
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add BlackBeltTechnology/pi-agent-dashboard --skill anti-slop-frontendDo not use when
Alternative
1.9K Stars
npx skills add yanliudesign/mono-color-skill --skill mono-color
Alternative
61.0K Stars
npx skills add mvanhorn/last30days-skill -g
Alternative
38.4K Stars
npx skills add Imbad0202/academic-research-skills
Alternative
28.0K Stars
npx skills add assafelovic/gpt-researcher
Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill may drive a browser or interact with web pages.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20anti-slop-frontend%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20anti-slop-frontend%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/blackbelttechnology-anti-slop-frontend/install
Agent should check
Copy prompt
Task: Use anti-slop-frontend in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20anti-slop-frontend%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/blackbelttechnology-anti-slop-frontend/install
Install command: npx skills add BlackBeltTechnology/pi-agent-dashboard --skill anti-slop-frontend
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/blackbelttechnology-anti-slop-frontend/install
LLM text format
/api/skills/blackbelttechnology-anti-slop-frontend/install?format=text
Find alternatives
/api/skills/search?q=anti-slop-frontend&limit=3
Agent prompt
Use anti-slop-frontend for this task. Review https://www.openagentskill.com/api/skills/blackbelttechnology-anti-slop-frontend/install, then install with: npx skills add BlackBeltTechnology/pi-agent-dashboard --skill anti-slop-frontendRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/blackbelttechnology-anti-slop-frontend
LLM text
/api/registry/manifest/blackbelttechnology-anti-slop-frontend?format=text
Install alias
/api/registry/install/blackbelttechnology-anti-slop-frontend
Recommend
/api/registry/recommend?task=Use%20anti-slop-frontend%20in%20an%20agent%20workflow&limit=3
Agent fit
Local desktop
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Local desktop
Trust label
Prototype first
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO270 GitHub stars
Stars/forks activity
CHECK270 stars, 38 forks; issue activity unavailable in current metadata
Recent maintenance
PASS2d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Workflow fit
Design, build, test, and ship interfaces
A practical workflow for agents that turn product briefs or Figma designs into polished frontend code, review the result, test it in a browser, and prepare a safe deployment.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Alternative shortlist
Similar skills that may fit this task.
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills for Claude Code: research → write → review → revise → finalize
Run autonomous deep research over web and local sources
--- name: anti-slop-frontend description: "A mechanical, countable anti-slop checklist for AI-generated frontend. Catches the specific signatures an undirected model defaults to: AI-purple glows, Inter-everywhere, em-dashes, div-based fake screenshots, eyebrow-on-every-section, beige+brass \"premium\" palettes, generic Jane Doe / Acme data. Advisory layer that pairs with frontend-mockup-loop (which owns the cite-a-source loop plus WCAG gates) but works standalone in any React/Tailwind/HTML project. Triggers: \"does this look AI-generated\", \"anti-slop pass\", \"remove the AI tells\", \"why does this look templated\", \"design review for slop\"." license: MIT metadata: author: blackbelt-technology version: "0.1" adapted_from: "Leonxlnx/taste-skill (design-taste-frontend, MIT) - countable rules distilled, stack-coupling removed, scoped universal vs marketing-only." ---
# anti-slop-frontend
A flat, **mechanical** checklist of the concrete signatures an undirected model emits when it tries to "look designed." Every rule here is **countable or binary** - you can mechanically verify pass/fail, not argue taste. That is the whole point: "it looks better" is not a check; "eyebrow count > ceil(sections/3)" is.
## What this is, and is NOT
- **IS** an advisory catalog of AI-tells, scoped by surface kind. - **IS** standalone - works with no tooling, in any React/Tailwind/HTML project. - **IS NOT** a design philosophy, a loop, or a gate. It scores; it never blocks.
### Relationship to `frontend-mockup-loop`
Different jobs, intentionally separate:
| | frontend-mockup-loop | anti-slop-frontend (this) | |---|---|---| | Shape | ground→contract→mockup→test→fix→learn **loop** | flat **checklist** | | Basis | cite an **external public rule** (Nielsen, WCAG, Laws of UX) | codified **AI-tell catalog** | | Authority | owns the **hard gates** (WCAG-AA, severity-4) | **advisory only**, drives the fix list | | Domain | product UI, dashboards, flows | universal tells + marketing-surface tells |
When both are present: the loop's a11y floor and cite-a-source rule **win**. This skill feeds concrete failing items into the loop's FIX step. It never overrides a gate, and a tell here is never a reason to violate a cited rule.
> **Honesty note:** these rules are curated *taste*, hardened into countable > form. They are good defaults, not laws of nature. Every rule has an **override > path**: when the brief explicitly asks for the "banned" thing, it is allowed - > execute it with intent, not by accident.
---
## The three dials (set once, up front)
State these before reviewing or generating. They gate which rules fire and how hard.
- **`VARIANCE` (1-10)** - 1 = perfect symmetry, 10 = artsy chaos - **`MOTION` (1-10)** - 1 = static, 10 = cinematic/physics - **`DENSITY` (1-10)** - 1 = art-gallery airy, 10 = cockpit/packed-data
Infer from the brief; don't silently use a baseline. Dashboards/data UI live high on DENSITY and low on VARIANCE/MOTION. Landing/portfolio live the opposite.
---
## PART A - Universal tells (apply to EVERY surface, dashboards included)
These fire regardless of surface kind. A dense admin panel is just as guilty of AI-purple and Inter-everywhere as a landing page.
### A1. Color - **No AI-purple/blue glow as default.** No automatic violet button glows, no random neon gradients ("the Lila tell"). Neutral base (Zinc/Slate/Stone) + ONE high-contrast accent. *Override:* brand literally is purple. - **Max 1 accent color, saturation < 80% default.** Lock it: the same accent on the whole page. A warm-grey UI does not grow a blue CTA in section 7. - **One neutral temperature per project.** Don't drift warm-grey ↔ cool-grey. - **No pure `#000000` / pure `#ffffff`.** Off-black (zinc-950) and off-white; pure values kill depth.
### A2. Typography - **Inter is discouraged as the *default*.** Reach past it (Geist, Outfit, Cabinet Grotesk, Satoshi) unless the brief wants neutral/Linear-style or is accessibility-first. *Override exists.* - **Serif is very discouraged as default.** "Feels premium/creative" is not a reason. Specifically banned as defaults: **Fraunces, Instrument Serif**. Serif only when the brief names one or the family is genuinely editorial/luxury/heritage. - **Emphasis = italic/bold of the SAME family.** Never inject a random serif word into a sans headline for "visual interest." - **One corner-radius scale per page** (all-sharp / all-soft / all-pill), or a documented rule followed everywhere.
### A3. The em-dash ban (the #1 tell) - **Zero `—` and zero `–`-as-separator anywhere visible.** Headlines, labels, pills, body, quotes, attribution, captions, buttons, alt text. No "sparingly." Replace with a period, comma, colon, parentheses, line break, or a spaced hyphen ` - `. Ranges use a plain hyphen (`2018-2026`, `€40-80k`). - Mechanical check: grep the rendered output for `—`/`–`. Any hit = fail.
### A4. Fake data ("Jane Doe" effect) - **No generic names.** "John Doe / Sarah Chan / Jack Su" → realistic, locale-appropriate names. - **No generic brand names.** "Acme / Nexus / SmartFlow / Cloudly" → contextual names that sound real. - **No fake-perfect numbers.** `99.99%`, `50%`, `1234567` → organic values (`47.2%`, real-looking phone formats). Fake-precise engineering specs (`5.8mm`, `4.1×`) are banned unless from real data or labeled mock. - **No filler verbs.** "Elevate / Seamless / Unleash / Next-Gen / Revolutionize" → concrete verbs. - **No generic avatars** (SVG "egg", default user glyph) → believable placeholders.
### A5. Assets & icons - **No div-based fake screenshots.** Building a fake dashboard/terminal/task-list out of styled `<div>`s is the single biggest tell. Use a real screenshot, a generated image, a real mini component preview, or nothing. - **No hand-rolled SVG icons.** Use one icon family (Phosphor / HugeIcons / Radix / Tabler), standardized stroke width. Lucide only on explicit request. - **No hand-rolled decorative SVG illustrations** as default. - **No broken image links.** Use `picsum.photos/seed/{descriptive}/{w}/{h}` or generated assets, never dead Unsplash URLs.
### A6. Interactive states (the "happy-path only" tell) - **Loading / empty / error states exist**, not just the static success state. Skeletons match final layout shape; avoid generic spinners. - **Button contrast (a11y).** Every CTA's text passes WCAG AA against its own background. No white-on-white, no transparent button on same-color bg with no border. *(This one is also a hard gate when frontend-mockup-loop runs.)* - **Form contrast (a11y).** Inputs, placeholders, focus rings, helper, error text all pass AA against the section bg. Label above input; never placeholder-as-label.
### A7. Motion must be motivated - **Every animation justifies itself in one sentence** - hierarchy, storytelling, feedback, or state-transition. "It looked cool" is not valid. Motion-for-show is amateur. - **Motion claimed = motion shown.** If `MOTION > 4`, the page actually moves; if you can't ship working motion, drop the dial and ship clean static. - **Banned mechanism: `window.addEventListener('scroll', …)`** and React-state scroll/rAF loops. Use scroll-driven CSS, IntersectionObserver, or a motion library's scroll primitives. - **Reduced-motion honored** for anything above `MOTION 3`.
---
## PART B - Marketing-surface tells (landing / portfolio / about ONLY)
Skip Part B entirely for dashboards, data tables, wizards, editors, product UI. These rules govern hero-driven marketing pages, where the model's worst templating habits live.
### B1. Hero discipline - **Hero fits the initial viewport.** Headline ≤ 2 lines, subtext ≤ 20 words and ≤ 4 lines, CTA visible without scroll. A 4-line headline is a font-size error. - **Hero top padding ≤ `pt-24` desktop** (content must not float mid-viewport). - **Max 4 text elements in the hero**: (eyebrow OR brand strip), headline, subtext, CTAs. Banned in hero: trust micro-strip, pricing teaser, tagline under CTAs, feature bullets, avatar row - those move to sections below. - **No version labels** (`V0.6`, `BETA`, `INVITE-ONLY`) unless the brief is a launch.
### B2. The eyebrow tell (#1 violated rule) - An "eyebrow" = small uppercase wide-tracking label above a section headline (`text-[11px] uppercase tracking-[0.18em]`). - **Max 1 eyebrow per 3 sections** (hero counts as 1). Mechanical check: count `uppercase tracking` micro-labels above headlines; fail if > ceil(sections/3). - **No section-number eyebrows** (`00 / INDEX`, `001 · Capabilities`, `06 · how it works`). The section's position already categorizes it. - **Default fix: drop the eyebrow.** The headline alone is enough.
### B3. Layout repetition - **No 3 equal feature cards.** The "three identical horizontal cards" row is the default. Use asymmetric grid, zig-zag, or a different family. - **Zigzag cap: max 2 consecutive image+text splits.** The 3rd in a row is a fail. - **Section-layout-repetition ban.** A layout family appears at most once. 8 sections → ≥ 4 distinct families. - **No split-header** ("big left headline + small right floating paragraph") as default. Stack headline over body instead. - **Bento: exact cell count, real rhythm, background diversity.** N items → N cells (no empty tiles); ≥ 2-3 cells have real visual variation (image, gradient, pattern), not all white-on-white text cards. - **Marquee: max one per page.**
### B4. CTA & social proof - **No duplicate CTA intent.** "Get in touch" + "Let's talk" + "Contact us" on one page = fail. One label per intent, everywhere. - **No CTA wraps to 2+ lines at desktop** (shorten label or widen button). - **Logo wall lives UNDER the hero, is logos only** (no industry labels beneath), uses real SVG marks (Simple Icons / devicon) or generated monograms, not plain text wordmarks.
### B5. Decoration tells (banned by default) - **No decoration text strip** at hero bottom (`BRAND. MOTION. SPATIAL.`). - **No locale / city / time / weather strips** (`LIS 14:23 · 18°C`) unless the brief is genuinely place- or timezone-focused. - **No scroll cues** (`Scroll`, `↓ scroll`, `Scroll to explore`). - **No version footers** (`v1.4.2`, `Build 0048`, `last sync 4s ago`) on marketing pages - those are devtool fixtures. - **The middle-dot `·` is rationed** (max 1 per metadata line; not the default separator for everything). - **No decorative status dots** before every nav item / row / badge. Only for real semantic state, sparingly. - **No pills/labels overlaid on images** and **no pretentious photo-credit captions** (`Field study no. 12 · Ines Caetano`) on stock/placeholder images. - **No poetic section labels** ("From the field", "Field notes", "On our desks") → plain functional labels or none. - **No `border-t` + `border-b` on every row** of a long list/spec table. Long lists (>5 items) use a real component (grouped chunks, card grid, tabs, scroll-snap), not a hairline-per-row `<ul>`.
### B6. Copy self-audit - Re-read every visible string. Flag and rewrite: grammatically broken phrases, unclear referents, cute-but-wrong wordplay, fake-craftsman micro-meta. Plain functional copy beats AI-cute copy.
---
## Mechanical pre-flight (the grep-able subset)
The rules below can be checked by string-search, not judgment. Run them last.
- [ ] **Em-dash:** zero `—` / `–`-as-separator in rendered output (A3). - [ ] **AI-purple:** no default violet glow/gradient unless brand-justified (A1). - [ ] **Accent lock:** one accent hex family across all sections (A1). - [ ] **Default font:** not Inter (unless justified); serif is not Fraunces / Instrument Serif (A2). - [ ] **Fake data:** no "Doe / Acme / 99.99% / Elevate" (A4). - [ ] **Fake screenshots:** no div-built product UI; no hand-rolled icon paths (A5). - [ ] **CTA/form contrast:** every CTA + input passes WCAG AA (A6). - [ ] **Motion:** no `addEventListener('scroll')`; reduced-motion present (A7). - [ ]
Source provenance
Decision snapshot
recent repository activity
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for anti-slop-frontend, ready for a manual X post.
anti-slop-frontend: A mechanical, countable anti-slop checklist for AI-generated frontend. Catches the specific s... 270 stars https://www.openagentskill.com/skills/blackbelttechnology-anti-slop-frontend?ref=x
Listing + install path for anti-slop-frontend: https://www.openagentskill.com/skills/blackbelttechnology-anti-slop-frontend?ref=x Install: npx skills add BlackBeltTechnology/pi-agent-dashboard --skill anti-slop-frontend
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Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
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[](https://www.openagentskill.com/skills/blackbelttechnology-anti-slop-frontend?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)BlackBeltTechnology
@blackbelttechnology
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Sandbox only
mono-color
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
1.9K StarsLast30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
61.0K StarsAcademic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
38.4K StarsGPT Researcher
Run autonomous deep research over web and local sources
28.0K StarsSandbox only
Install targets
Codex install prompt
Install the "anti-slop-frontend" agent skill from https://github.com/BlackBeltTechnology/pi-agent-dashboard/tree/develop/packages/anti-slop/.pi/skills/anti-slop-frontend. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: A mechanical, countable anti-slop checklist for AI-generated frontend. Catches the specific signatures an undirected model defaults to: AI-purple glows, Inter-everywhere, em-dashes, div-based fake screenshots, eyebrow-on-every-section, beige+brass \"premium\" palettes, generic Jane Doe / Acme data. Advisory layer that pairs with frontend-mockup-loop (which owns the cite-a-source loop plus WCAG gates) but works standalone in any React/Tailwind/HTML project. Triggers: \"does this look AI-generated\", \"anti-slop pass\", \"remove the AI tells\", \"why does this look templated\", \"design review for slop\". After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"blackbelttechnology-anti-slop-frontend","task":"Install anti-slop-frontend","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add BlackBeltTechnology/pi-agent-dashboard --skill anti-slop-frontend
Maintenance
fresh
2d since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
270
71/100 Quality · 77/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · Financial research output is not financial advice; require human review before any live investment decision.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
270 GitHub stars
Repo activity
270 stars, 38 forks
Maintenance
2d since push
License
MIT
Install
npx skills add BlackBeltTechnology/pi-agent-dashboard --skill anti-slop-frontend
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add BlackBeltTechnology/pi-agent-dashboard --skill anti-slop-frontendDo not use when
Alternative
1.9K Stars
npx skills add yanliudesign/mono-color-skill --skill mono-color
Alternative
61.0K Stars
npx skills add mvanhorn/last30days-skill -g
Alternative
38.4K Stars
npx skills add Imbad0202/academic-research-skills
Alternative
28.0K Stars
npx skills add assafelovic/gpt-researcher
Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill may drive a browser or interact with web pages.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20anti-slop-frontend%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20anti-slop-frontend%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/blackbelttechnology-anti-slop-frontend/install
Agent should check
Copy prompt
Task: Use anti-slop-frontend in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20anti-slop-frontend%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/blackbelttechnology-anti-slop-frontend/install
Install command: npx skills add BlackBeltTechnology/pi-agent-dashboard --skill anti-slop-frontend
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/blackbelttechnology-anti-slop-frontend/install
LLM text format
/api/skills/blackbelttechnology-anti-slop-frontend/install?format=text
Find alternatives
/api/skills/search?q=anti-slop-frontend&limit=3
Agent prompt
Use anti-slop-frontend for this task. Review https://www.openagentskill.com/api/skills/blackbelttechnology-anti-slop-frontend/install, then install with: npx skills add BlackBeltTechnology/pi-agent-dashboard --skill anti-slop-frontendRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/blackbelttechnology-anti-slop-frontend
LLM text
/api/registry/manifest/blackbelttechnology-anti-slop-frontend?format=text
Install alias
/api/registry/install/blackbelttechnology-anti-slop-frontend
Recommend
/api/registry/recommend?task=Use%20anti-slop-frontend%20in%20an%20agent%20workflow&limit=3
Agent fit
Local desktop
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Local desktop
Trust label
Prototype first
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO270 GitHub stars
Stars/forks activity
CHECK270 stars, 38 forks; issue activity unavailable in current metadata
Recent maintenance
PASS2d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Workflow fit
Design, build, test, and ship interfaces
A practical workflow for agents that turn product briefs or Figma designs into polished frontend code, review the result, test it in a browser, and prepare a safe deployment.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Alternative shortlist
Similar skills that may fit this task.
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills for Claude Code: research → write → review → revise → finalize
Run autonomous deep research over web and local sources
--- name: anti-slop-frontend description: "A mechanical, countable anti-slop checklist for AI-generated frontend. Catches the specific signatures an undirected model defaults to: AI-purple glows, Inter-everywhere, em-dashes, div-based fake screenshots, eyebrow-on-every-section, beige+brass \"premium\" palettes, generic Jane Doe / Acme data. Advisory layer that pairs with frontend-mockup-loop (which owns the cite-a-source loop plus WCAG gates) but works standalone in any React/Tailwind/HTML project. Triggers: \"does this look AI-generated\", \"anti-slop pass\", \"remove the AI tells\", \"why does this look templated\", \"design review for slop\"." license: MIT metadata: author: blackbelt-technology version: "0.1" adapted_from: "Leonxlnx/taste-skill (design-taste-frontend, MIT) - countable rules distilled, stack-coupling removed, scoped universal vs marketing-only." ---
# anti-slop-frontend
A flat, **mechanical** checklist of the concrete signatures an undirected model emits when it tries to "look designed." Every rule here is **countable or binary** - you can mechanically verify pass/fail, not argue taste. That is the whole point: "it looks better" is not a check; "eyebrow count > ceil(sections/3)" is.
## What this is, and is NOT
- **IS** an advisory catalog of AI-tells, scoped by surface kind. - **IS** standalone - works with no tooling, in any React/Tailwind/HTML project. - **IS NOT** a design philosophy, a loop, or a gate. It scores; it never blocks.
### Relationship to `frontend-mockup-loop`
Different jobs, intentionally separate:
| | frontend-mockup-loop | anti-slop-frontend (this) | |---|---|---| | Shape | ground→contract→mockup→test→fix→learn **loop** | flat **checklist** | | Basis | cite an **external public rule** (Nielsen, WCAG, Laws of UX) | codified **AI-tell catalog** | | Authority | owns the **hard gates** (WCAG-AA, severity-4) | **advisory only**, drives the fix list | | Domain | product UI, dashboards, flows | universal tells + marketing-surface tells |
When both are present: the loop's a11y floor and cite-a-source rule **win**. This skill feeds concrete failing items into the loop's FIX step. It never overrides a gate, and a tell here is never a reason to violate a cited rule.
> **Honesty note:** these rules are curated *taste*, hardened into countable > form. They are good defaults, not laws of nature. Every rule has an **override > path**: when the brief explicitly asks for the "banned" thing, it is allowed - > execute it with intent, not by accident.
---
## The three dials (set once, up front)
State these before reviewing or generating. They gate which rules fire and how hard.
- **`VARIANCE` (1-10)** - 1 = perfect symmetry, 10 = artsy chaos - **`MOTION` (1-10)** - 1 = static, 10 = cinematic/physics - **`DENSITY` (1-10)** - 1 = art-gallery airy, 10 = cockpit/packed-data
Infer from the brief; don't silently use a baseline. Dashboards/data UI live high on DENSITY and low on VARIANCE/MOTION. Landing/portfolio live the opposite.
---
## PART A - Universal tells (apply to EVERY surface, dashboards included)
These fire regardless of surface kind. A dense admin panel is just as guilty of AI-purple and Inter-everywhere as a landing page.
### A1. Color - **No AI-purple/blue glow as default.** No automatic violet button glows, no random neon gradients ("the Lila tell"). Neutral base (Zinc/Slate/Stone) + ONE high-contrast accent. *Override:* brand literally is purple. - **Max 1 accent color, saturation < 80% default.** Lock it: the same accent on the whole page. A warm-grey UI does not grow a blue CTA in section 7. - **One neutral temperature per project.** Don't drift warm-grey ↔ cool-grey. - **No pure `#000000` / pure `#ffffff`.** Off-black (zinc-950) and off-white; pure values kill depth.
### A2. Typography - **Inter is discouraged as the *default*.** Reach past it (Geist, Outfit, Cabinet Grotesk, Satoshi) unless the brief wants neutral/Linear-style or is accessibility-first. *Override exists.* - **Serif is very discouraged as default.** "Feels premium/creative" is not a reason. Specifically banned as defaults: **Fraunces, Instrument Serif**. Serif only when the brief names one or the family is genuinely editorial/luxury/heritage. - **Emphasis = italic/bold of the SAME family.** Never inject a random serif word into a sans headline for "visual interest." - **One corner-radius scale per page** (all-sharp / all-soft / all-pill), or a documented rule followed everywhere.
### A3. The em-dash ban (the #1 tell) - **Zero `—` and zero `–`-as-separator anywhere visible.** Headlines, labels, pills, body, quotes, attribution, captions, buttons, alt text. No "sparingly." Replace with a period, comma, colon, parentheses, line break, or a spaced hyphen ` - `. Ranges use a plain hyphen (`2018-2026`, `€40-80k`). - Mechanical check: grep the rendered output for `—`/`–`. Any hit = fail.
### A4. Fake data ("Jane Doe" effect) - **No generic names.** "John Doe / Sarah Chan / Jack Su" → realistic, locale-appropriate names. - **No generic brand names.** "Acme / Nexus / SmartFlow / Cloudly" → contextual names that sound real. - **No fake-perfect numbers.** `99.99%`, `50%`, `1234567` → organic values (`47.2%`, real-looking phone formats). Fake-precise engineering specs (`5.8mm`, `4.1×`) are banned unless from real data or labeled mock. - **No filler verbs.** "Elevate / Seamless / Unleash / Next-Gen / Revolutionize" → concrete verbs. - **No generic avatars** (SVG "egg", default user glyph) → believable placeholders.
### A5. Assets & icons - **No div-based fake screenshots.** Building a fake dashboard/terminal/task-list out of styled `<div>`s is the single biggest tell. Use a real screenshot, a generated image, a real mini component preview, or nothing. - **No hand-rolled SVG icons.** Use one icon family (Phosphor / HugeIcons / Radix / Tabler), standardized stroke width. Lucide only on explicit request. - **No hand-rolled decorative SVG illustrations** as default. - **No broken image links.** Use `picsum.photos/seed/{descriptive}/{w}/{h}` or generated assets, never dead Unsplash URLs.
### A6. Interactive states (the "happy-path only" tell) - **Loading / empty / error states exist**, not just the static success state. Skeletons match final layout shape; avoid generic spinners. - **Button contrast (a11y).** Every CTA's text passes WCAG AA against its own background. No white-on-white, no transparent button on same-color bg with no border. *(This one is also a hard gate when frontend-mockup-loop runs.)* - **Form contrast (a11y).** Inputs, placeholders, focus rings, helper, error text all pass AA against the section bg. Label above input; never placeholder-as-label.
### A7. Motion must be motivated - **Every animation justifies itself in one sentence** - hierarchy, storytelling, feedback, or state-transition. "It looked cool" is not valid. Motion-for-show is amateur. - **Motion claimed = motion shown.** If `MOTION > 4`, the page actually moves; if you can't ship working motion, drop the dial and ship clean static. - **Banned mechanism: `window.addEventListener('scroll', …)`** and React-state scroll/rAF loops. Use scroll-driven CSS, IntersectionObserver, or a motion library's scroll primitives. - **Reduced-motion honored** for anything above `MOTION 3`.
---
## PART B - Marketing-surface tells (landing / portfolio / about ONLY)
Skip Part B entirely for dashboards, data tables, wizards, editors, product UI. These rules govern hero-driven marketing pages, where the model's worst templating habits live.
### B1. Hero discipline - **Hero fits the initial viewport.** Headline ≤ 2 lines, subtext ≤ 20 words and ≤ 4 lines, CTA visible without scroll. A 4-line headline is a font-size error. - **Hero top padding ≤ `pt-24` desktop** (content must not float mid-viewport). - **Max 4 text elements in the hero**: (eyebrow OR brand strip), headline, subtext, CTAs. Banned in hero: trust micro-strip, pricing teaser, tagline under CTAs, feature bullets, avatar row - those move to sections below. - **No version labels** (`V0.6`, `BETA`, `INVITE-ONLY`) unless the brief is a launch.
### B2. The eyebrow tell (#1 violated rule) - An "eyebrow" = small uppercase wide-tracking label above a section headline (`text-[11px] uppercase tracking-[0.18em]`). - **Max 1 eyebrow per 3 sections** (hero counts as 1). Mechanical check: count `uppercase tracking` micro-labels above headlines; fail if > ceil(sections/3). - **No section-number eyebrows** (`00 / INDEX`, `001 · Capabilities`, `06 · how it works`). The section's position already categorizes it. - **Default fix: drop the eyebrow.** The headline alone is enough.
### B3. Layout repetition - **No 3 equal feature cards.** The "three identical horizontal cards" row is the default. Use asymmetric grid, zig-zag, or a different family. - **Zigzag cap: max 2 consecutive image+text splits.** The 3rd in a row is a fail. - **Section-layout-repetition ban.** A layout family appears at most once. 8 sections → ≥ 4 distinct families. - **No split-header** ("big left headline + small right floating paragraph") as default. Stack headline over body instead. - **Bento: exact cell count, real rhythm, background diversity.** N items → N cells (no empty tiles); ≥ 2-3 cells have real visual variation (image, gradient, pattern), not all white-on-white text cards. - **Marquee: max one per page.**
### B4. CTA & social proof - **No duplicate CTA intent.** "Get in touch" + "Let's talk" + "Contact us" on one page = fail. One label per intent, everywhere. - **No CTA wraps to 2+ lines at desktop** (shorten label or widen button). - **Logo wall lives UNDER the hero, is logos only** (no industry labels beneath), uses real SVG marks (Simple Icons / devicon) or generated monograms, not plain text wordmarks.
### B5. Decoration tells (banned by default) - **No decoration text strip** at hero bottom (`BRAND. MOTION. SPATIAL.`). - **No locale / city / time / weather strips** (`LIS 14:23 · 18°C`) unless the brief is genuinely place- or timezone-focused. - **No scroll cues** (`Scroll`, `↓ scroll`, `Scroll to explore`). - **No version footers** (`v1.4.2`, `Build 0048`, `last sync 4s ago`) on marketing pages - those are devtool fixtures. - **The middle-dot `·` is rationed** (max 1 per metadata line; not the default separator for everything). - **No decorative status dots** before every nav item / row / badge. Only for real semantic state, sparingly. - **No pills/labels overlaid on images** and **no pretentious photo-credit captions** (`Field study no. 12 · Ines Caetano`) on stock/placeholder images. - **No poetic section labels** ("From the field", "Field notes", "On our desks") → plain functional labels or none. - **No `border-t` + `border-b` on every row** of a long list/spec table. Long lists (>5 items) use a real component (grouped chunks, card grid, tabs, scroll-snap), not a hairline-per-row `<ul>`.
### B6. Copy self-audit - Re-read every visible string. Flag and rewrite: grammatically broken phrases, unclear referents, cute-but-wrong wordplay, fake-craftsman micro-meta. Plain functional copy beats AI-cute copy.
---
## Mechanical pre-flight (the grep-able subset)
The rules below can be checked by string-search, not judgment. Run them last.
- [ ] **Em-dash:** zero `—` / `–`-as-separator in rendered output (A3). - [ ] **AI-purple:** no default violet glow/gradient unless brand-justified (A1). - [ ] **Accent lock:** one accent hex family across all sections (A1). - [ ] **Default font:** not Inter (unless justified); serif is not Fraunces / Instrument Serif (A2). - [ ] **Fake data:** no "Doe / Acme / 99.99% / Elevate" (A4). - [ ] **Fake screenshots:** no div-built product UI; no hand-rolled icon paths (A5). - [ ] **CTA/form contrast:** every CTA + input passes WCAG AA (A6). - [ ] **Motion:** no `addEventListener('scroll')`; reduced-motion present (A7). - [ ]
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Scenario-led draft for anti-slop-frontend, ready for a manual X post.
anti-slop-frontend: A mechanical, countable anti-slop checklist for AI-generated frontend. Catches the specific s... 270 stars https://www.openagentskill.com/skills/blackbelttechnology-anti-slop-frontend?ref=x
Listing + install path for anti-slop-frontend: https://www.openagentskill.com/skills/blackbelttechnology-anti-slop-frontend?ref=x Install: npx skills add BlackBeltTechnology/pi-agent-dashboard --skill anti-slop-frontend
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[](https://www.openagentskill.com/skills/blackbelttechnology-anti-slop-frontend?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)BlackBeltTechnology
@blackbelttechnology
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mono-color
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
1.9K StarsLast30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
61.0K StarsAcademic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
38.4K StarsGPT Researcher
Run autonomous deep research over web and local sources
28.0K StarsSandbox only
Install targets
Codex install prompt
Install the "anti-slop-frontend" agent skill from https://github.com/BlackBeltTechnology/pi-agent-dashboard/tree/develop/packages/anti-slop/.pi/skills/anti-slop-frontend. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: A mechanical, countable anti-slop checklist for AI-generated frontend. Catches the specific signatures an undirected model defaults to: AI-purple glows, Inter-everywhere, em-dashes, div-based fake screenshots, eyebrow-on-every-section, beige+brass \"premium\" palettes, generic Jane Doe / Acme data. Advisory layer that pairs with frontend-mockup-loop (which owns the cite-a-source loop plus WCAG gates) but works standalone in any React/Tailwind/HTML project. Triggers: \"does this look AI-generated\", \"anti-slop pass\", \"remove the AI tells\", \"why does this look templated\", \"design review for slop\". After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"blackbelttechnology-anti-slop-frontend","task":"Install anti-slop-frontend","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
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Ready
npx skills add BlackBeltTechnology/pi-agent-dashboard --skill anti-slop-frontend
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fresh
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Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
270
71/100 Quality · 77/100 Trust
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Review notes
Financial research output is not financial advice; require human review before any live investment decision · Financial research output is not financial advice; require human review before any live investment decision.
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Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
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Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
270 GitHub stars
Repo activity
270 stars, 38 forks
Maintenance
2d since push
License
MIT
Install
npx skills add BlackBeltTechnology/pi-agent-dashboard --skill anti-slop-frontend
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Install command
npx skills add BlackBeltTechnology/pi-agent-dashboard --skill anti-slop-frontendDo not use when
Alternative
1.9K Stars
npx skills add yanliudesign/mono-color-skill --skill mono-color
Alternative
61.0K Stars
npx skills add mvanhorn/last30days-skill -g
Alternative
38.4K Stars
npx skills add Imbad0202/academic-research-skills
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28.0K Stars
npx skills add assafelovic/gpt-researcher
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Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill may drive a browser or interact with web pages.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
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/api/agent/resolve?task=Use%20anti-slop-frontend%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20anti-slop-frontend%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
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/api/skills/blackbelttechnology-anti-slop-frontend/install
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Task: Use anti-slop-frontend in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20anti-slop-frontend%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/blackbelttechnology-anti-slop-frontend/install
Install command: npx skills add BlackBeltTechnology/pi-agent-dashboard --skill anti-slop-frontend
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
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/api/skills/blackbelttechnology-anti-slop-frontend/install
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/api/skills/blackbelttechnology-anti-slop-frontend/install?format=text
Find alternatives
/api/skills/search?q=anti-slop-frontend&limit=3
Agent prompt
Use anti-slop-frontend for this task. Review https://www.openagentskill.com/api/skills/blackbelttechnology-anti-slop-frontend/install, then install with: npx skills add BlackBeltTechnology/pi-agent-dashboard --skill anti-slop-frontendRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/blackbelttechnology-anti-slop-frontend
LLM text
/api/registry/manifest/blackbelttechnology-anti-slop-frontend?format=text
Install alias
/api/registry/install/blackbelttechnology-anti-slop-frontend
Recommend
/api/registry/recommend?task=Use%20anti-slop-frontend%20in%20an%20agent%20workflow&limit=3
Agent fit
Local desktop
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Prototype with this skill first; keep a fallback candidate ready.
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Fallback candidate
Primary fit
Local desktop
Trust label
Prototype first
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Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO270 GitHub stars
Stars/forks activity
CHECK270 stars, 38 forks; issue activity unavailable in current metadata
Recent maintenance
PASS2d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Workflow fit
Design, build, test, and ship interfaces
A practical workflow for agents that turn product briefs or Figma designs into polished frontend code, review the result, test it in a browser, and prepare a safe deployment.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Alternative shortlist
Similar skills that may fit this task.
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills for Claude Code: research → write → review → revise → finalize
Run autonomous deep research over web and local sources
--- name: anti-slop-frontend description: "A mechanical, countable anti-slop checklist for AI-generated frontend. Catches the specific signatures an undirected model defaults to: AI-purple glows, Inter-everywhere, em-dashes, div-based fake screenshots, eyebrow-on-every-section, beige+brass \"premium\" palettes, generic Jane Doe / Acme data. Advisory layer that pairs with frontend-mockup-loop (which owns the cite-a-source loop plus WCAG gates) but works standalone in any React/Tailwind/HTML project. Triggers: \"does this look AI-generated\", \"anti-slop pass\", \"remove the AI tells\", \"why does this look templated\", \"design review for slop\"." license: MIT metadata: author: blackbelt-technology version: "0.1" adapted_from: "Leonxlnx/taste-skill (design-taste-frontend, MIT) - countable rules distilled, stack-coupling removed, scoped universal vs marketing-only." ---
# anti-slop-frontend
A flat, **mechanical** checklist of the concrete signatures an undirected model emits when it tries to "look designed." Every rule here is **countable or binary** - you can mechanically verify pass/fail, not argue taste. That is the whole point: "it looks better" is not a check; "eyebrow count > ceil(sections/3)" is.
## What this is, and is NOT
- **IS** an advisory catalog of AI-tells, scoped by surface kind. - **IS** standalone - works with no tooling, in any React/Tailwind/HTML project. - **IS NOT** a design philosophy, a loop, or a gate. It scores; it never blocks.
### Relationship to `frontend-mockup-loop`
Different jobs, intentionally separate:
| | frontend-mockup-loop | anti-slop-frontend (this) | |---|---|---| | Shape | ground→contract→mockup→test→fix→learn **loop** | flat **checklist** | | Basis | cite an **external public rule** (Nielsen, WCAG, Laws of UX) | codified **AI-tell catalog** | | Authority | owns the **hard gates** (WCAG-AA, severity-4) | **advisory only**, drives the fix list | | Domain | product UI, dashboards, flows | universal tells + marketing-surface tells |
When both are present: the loop's a11y floor and cite-a-source rule **win**. This skill feeds concrete failing items into the loop's FIX step. It never overrides a gate, and a tell here is never a reason to violate a cited rule.
> **Honesty note:** these rules are curated *taste*, hardened into countable > form. They are good defaults, not laws of nature. Every rule has an **override > path**: when the brief explicitly asks for the "banned" thing, it is allowed - > execute it with intent, not by accident.
---
## The three dials (set once, up front)
State these before reviewing or generating. They gate which rules fire and how hard.
- **`VARIANCE` (1-10)** - 1 = perfect symmetry, 10 = artsy chaos - **`MOTION` (1-10)** - 1 = static, 10 = cinematic/physics - **`DENSITY` (1-10)** - 1 = art-gallery airy, 10 = cockpit/packed-data
Infer from the brief; don't silently use a baseline. Dashboards/data UI live high on DENSITY and low on VARIANCE/MOTION. Landing/portfolio live the opposite.
---
## PART A - Universal tells (apply to EVERY surface, dashboards included)
These fire regardless of surface kind. A dense admin panel is just as guilty of AI-purple and Inter-everywhere as a landing page.
### A1. Color - **No AI-purple/blue glow as default.** No automatic violet button glows, no random neon gradients ("the Lila tell"). Neutral base (Zinc/Slate/Stone) + ONE high-contrast accent. *Override:* brand literally is purple. - **Max 1 accent color, saturation < 80% default.** Lock it: the same accent on the whole page. A warm-grey UI does not grow a blue CTA in section 7. - **One neutral temperature per project.** Don't drift warm-grey ↔ cool-grey. - **No pure `#000000` / pure `#ffffff`.** Off-black (zinc-950) and off-white; pure values kill depth.
### A2. Typography - **Inter is discouraged as the *default*.** Reach past it (Geist, Outfit, Cabinet Grotesk, Satoshi) unless the brief wants neutral/Linear-style or is accessibility-first. *Override exists.* - **Serif is very discouraged as default.** "Feels premium/creative" is not a reason. Specifically banned as defaults: **Fraunces, Instrument Serif**. Serif only when the brief names one or the family is genuinely editorial/luxury/heritage. - **Emphasis = italic/bold of the SAME family.** Never inject a random serif word into a sans headline for "visual interest." - **One corner-radius scale per page** (all-sharp / all-soft / all-pill), or a documented rule followed everywhere.
### A3. The em-dash ban (the #1 tell) - **Zero `—` and zero `–`-as-separator anywhere visible.** Headlines, labels, pills, body, quotes, attribution, captions, buttons, alt text. No "sparingly." Replace with a period, comma, colon, parentheses, line break, or a spaced hyphen ` - `. Ranges use a plain hyphen (`2018-2026`, `€40-80k`). - Mechanical check: grep the rendered output for `—`/`–`. Any hit = fail.
### A4. Fake data ("Jane Doe" effect) - **No generic names.** "John Doe / Sarah Chan / Jack Su" → realistic, locale-appropriate names. - **No generic brand names.** "Acme / Nexus / SmartFlow / Cloudly" → contextual names that sound real. - **No fake-perfect numbers.** `99.99%`, `50%`, `1234567` → organic values (`47.2%`, real-looking phone formats). Fake-precise engineering specs (`5.8mm`, `4.1×`) are banned unless from real data or labeled mock. - **No filler verbs.** "Elevate / Seamless / Unleash / Next-Gen / Revolutionize" → concrete verbs. - **No generic avatars** (SVG "egg", default user glyph) → believable placeholders.
### A5. Assets & icons - **No div-based fake screenshots.** Building a fake dashboard/terminal/task-list out of styled `<div>`s is the single biggest tell. Use a real screenshot, a generated image, a real mini component preview, or nothing. - **No hand-rolled SVG icons.** Use one icon family (Phosphor / HugeIcons / Radix / Tabler), standardized stroke width. Lucide only on explicit request. - **No hand-rolled decorative SVG illustrations** as default. - **No broken image links.** Use `picsum.photos/seed/{descriptive}/{w}/{h}` or generated assets, never dead Unsplash URLs.
### A6. Interactive states (the "happy-path only" tell) - **Loading / empty / error states exist**, not just the static success state. Skeletons match final layout shape; avoid generic spinners. - **Button contrast (a11y).** Every CTA's text passes WCAG AA against its own background. No white-on-white, no transparent button on same-color bg with no border. *(This one is also a hard gate when frontend-mockup-loop runs.)* - **Form contrast (a11y).** Inputs, placeholders, focus rings, helper, error text all pass AA against the section bg. Label above input; never placeholder-as-label.
### A7. Motion must be motivated - **Every animation justifies itself in one sentence** - hierarchy, storytelling, feedback, or state-transition. "It looked cool" is not valid. Motion-for-show is amateur. - **Motion claimed = motion shown.** If `MOTION > 4`, the page actually moves; if you can't ship working motion, drop the dial and ship clean static. - **Banned mechanism: `window.addEventListener('scroll', …)`** and React-state scroll/rAF loops. Use scroll-driven CSS, IntersectionObserver, or a motion library's scroll primitives. - **Reduced-motion honored** for anything above `MOTION 3`.
---
## PART B - Marketing-surface tells (landing / portfolio / about ONLY)
Skip Part B entirely for dashboards, data tables, wizards, editors, product UI. These rules govern hero-driven marketing pages, where the model's worst templating habits live.
### B1. Hero discipline - **Hero fits the initial viewport.** Headline ≤ 2 lines, subtext ≤ 20 words and ≤ 4 lines, CTA visible without scroll. A 4-line headline is a font-size error. - **Hero top padding ≤ `pt-24` desktop** (content must not float mid-viewport). - **Max 4 text elements in the hero**: (eyebrow OR brand strip), headline, subtext, CTAs. Banned in hero: trust micro-strip, pricing teaser, tagline under CTAs, feature bullets, avatar row - those move to sections below. - **No version labels** (`V0.6`, `BETA`, `INVITE-ONLY`) unless the brief is a launch.
### B2. The eyebrow tell (#1 violated rule) - An "eyebrow" = small uppercase wide-tracking label above a section headline (`text-[11px] uppercase tracking-[0.18em]`). - **Max 1 eyebrow per 3 sections** (hero counts as 1). Mechanical check: count `uppercase tracking` micro-labels above headlines; fail if > ceil(sections/3). - **No section-number eyebrows** (`00 / INDEX`, `001 · Capabilities`, `06 · how it works`). The section's position already categorizes it. - **Default fix: drop the eyebrow.** The headline alone is enough.
### B3. Layout repetition - **No 3 equal feature cards.** The "three identical horizontal cards" row is the default. Use asymmetric grid, zig-zag, or a different family. - **Zigzag cap: max 2 consecutive image+text splits.** The 3rd in a row is a fail. - **Section-layout-repetition ban.** A layout family appears at most once. 8 sections → ≥ 4 distinct families. - **No split-header** ("big left headline + small right floating paragraph") as default. Stack headline over body instead. - **Bento: exact cell count, real rhythm, background diversity.** N items → N cells (no empty tiles); ≥ 2-3 cells have real visual variation (image, gradient, pattern), not all white-on-white text cards. - **Marquee: max one per page.**
### B4. CTA & social proof - **No duplicate CTA intent.** "Get in touch" + "Let's talk" + "Contact us" on one page = fail. One label per intent, everywhere. - **No CTA wraps to 2+ lines at desktop** (shorten label or widen button). - **Logo wall lives UNDER the hero, is logos only** (no industry labels beneath), uses real SVG marks (Simple Icons / devicon) or generated monograms, not plain text wordmarks.
### B5. Decoration tells (banned by default) - **No decoration text strip** at hero bottom (`BRAND. MOTION. SPATIAL.`). - **No locale / city / time / weather strips** (`LIS 14:23 · 18°C`) unless the brief is genuinely place- or timezone-focused. - **No scroll cues** (`Scroll`, `↓ scroll`, `Scroll to explore`). - **No version footers** (`v1.4.2`, `Build 0048`, `last sync 4s ago`) on marketing pages - those are devtool fixtures. - **The middle-dot `·` is rationed** (max 1 per metadata line; not the default separator for everything). - **No decorative status dots** before every nav item / row / badge. Only for real semantic state, sparingly. - **No pills/labels overlaid on images** and **no pretentious photo-credit captions** (`Field study no. 12 · Ines Caetano`) on stock/placeholder images. - **No poetic section labels** ("From the field", "Field notes", "On our desks") → plain functional labels or none. - **No `border-t` + `border-b` on every row** of a long list/spec table. Long lists (>5 items) use a real component (grouped chunks, card grid, tabs, scroll-snap), not a hairline-per-row `<ul>`.
### B6. Copy self-audit - Re-read every visible string. Flag and rewrite: grammatically broken phrases, unclear referents, cute-but-wrong wordplay, fake-craftsman micro-meta. Plain functional copy beats AI-cute copy.
---
## Mechanical pre-flight (the grep-able subset)
The rules below can be checked by string-search, not judgment. Run them last.
- [ ] **Em-dash:** zero `—` / `–`-as-separator in rendered output (A3). - [ ] **AI-purple:** no default violet glow/gradient unless brand-justified (A1). - [ ] **Accent lock:** one accent hex family across all sections (A1). - [ ] **Default font:** not Inter (unless justified); serif is not Fraunces / Instrument Serif (A2). - [ ] **Fake data:** no "Doe / Acme / 99.99% / Elevate" (A4). - [ ] **Fake screenshots:** no div-built product UI; no hand-rolled icon paths (A5). - [ ] **CTA/form contrast:** every CTA + input passes WCAG AA (A6). - [ ] **Motion:** no `addEventListener('scroll')`; reduced-motion present (A7). - [ ]
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mono-color
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
1.9K StarsLast30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
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Academic Research Skills for Claude Code: research → write → review → revise → finalize
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Run autonomous deep research over web and local sources
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shell or command execution
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