Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add jnPiyush/AgentX --skill anti-slopgit clone --depth 1 https://github.com/jnPiyush/AgentXWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jnpiyush/agentx/anti-slop)<a href="https://agentmods.dev/skills/jnpiyush/agentx/anti-slop"><img src="https://agentmods.dev/badge/skills/jnpiyush/agentx/anti-slop/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jnpiyush/agentx/anti-slop"><img src="https://agentmods.dev/badge/skills/jnpiyush/agentx/anti-slop.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00090 | $0.02717 |
| Opus 5.5 | $0.00036 | $0.01087 |
| Sonnet 5.5 | $0.00018 | $0.00543 |
| Haiku 4.5 | $0.00009 | $0.00272 |
Grade A, and why
anti-slop scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 257 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Anti-Slop
WHEN: After any AI-generated UI surface is produced -- prototype, marketing page, dashboard, or component library. This skill is a NAMED BLACKLIST plus a placeholder-honesty rule. Findings are concrete: each rule cites the visible symptom and the corrective replacement.
When to Use This Skill
- After UX Designer or Engineer agents emit HTML/CSS
- Before declaring a prototype review-ready (Pass 9 of prototype-audit)
- During Reviewer's visual-pass on a UI-bearing PR
- When a user feedback says the UI feels "generic" or "AI-made"
The Forbidden Tells
These are the patterns that mark a UI as AI-generated. Each is treated as a P0 finding -- the audit BLOCKS until the tell is removed or an explicit waiver is recorded with rationale.
Ownership: delegated vs retained
Five tells now have a deterministic rule in the Impeccable detector, which runs
as Pass 0 of prototype-audit before any LLM judgement. T6 is delegated to
Impeccable's judgement-based critique. Four tells stay Frontier-owned because
they concern fabrication and emoji rather than visual style.
| Tell | Owner | Deterministic rule |
|---|---|---|
| T1 purple-teal-pink gradient | delegated | AI color palette |
| T4 hand-drawn cartoon humans | delegated | Amateurish hand-drawn SVG, Shape-assembled illustration |
| T5 rounded-2xl everything | delegated | Extreme border-radius, Radius outside DESIGN.md |
| T6 glassmorphism on text | delegated judgement | Glassmorphism everywhere |
| T7 aurora background blobs | delegated | Radial halo, Decorative spotlight glow |
| T9 AI-voiced microcopy | delegated | Buzzword, Aphoristic cadence, Em-dash overuse, Theater framing |
| T2 generic system emoji | Frontier | none upstream |
| T3 fake metrics and testimonials | Frontier | none upstream |
| T8 unearned trust badges | Frontier | none upstream |
| T10 emoji-prefixed headings | Frontier | none upstream |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago Changed e1c1ebac7ca6
- 1mo ago First seen · 257 lines · 90 tokens per session scan A 054bd4e12ff5
anti-slop is a skill published in the GitHub repository jnPiyush/AgentX (16 stars, last pushed 3d ago), licensed Apache-2.0. It adds 90 tokens to every session and 2,717 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
webgl-holographic-foil
A self-contained WebGL2 hero: thin-film interference over a crushed-foil surface whose palette shifts with the viewing angle; move the cursor to tilt the film.
html-ppt-hermes-cyber-terminal
OpenDesign + BYOK: choosing and wiring your own model, hands-on — cost, quality, and the routing decision. Built as a decision-grade AI literacy deck for engineers, IT, applied-AI teams.
html-ppt-taste-brutalist
16:9 HTML deck in tactical-telemetry / CRT-terminal taste. Deactivated-CRT charcoal slides, white-phosphor monospace, hazard-red accent, scanline overlay, ASCII syntax, density over decoration. Distilled from Leonxlnx/taste-skill brutalist-skill (Tactical Telemetry mode).
visual-ralph
Visual Ralph orchestration for frontend UI from generated references, static references, or live URL targets, using $ultragoal with built-in visual verdict and pixel-diff evidence until the implementation matches and leaves a reproducible design system.
glance-canonical-layouts
Use this skill to create home screen widgets using Jetpack Glance Canonical Layouts from the Android Platform Samples project, or when asked to implement standard widget layout patterns (including Check List, Image Grid, Snap Scrolling, and Standard Toolbar).
accessibility
Consolidated accessibility skill entrypoint for WCAG 2.2, ARIA Authoring Practices, cognitive accessibility, Section 508, EN 301 549, design intent verification, and the Accessibility Planner workflow.