Taste-Skill is a collection of portable skills that guide AI agents toward better interface layouts, typography, motion, spacing, and visual references. It is used with coding agents such as Codex, Cursor, and Claude Code when building frontends. The catalogue entries are its own skills, instructions, and plugin for applying these design workflows.
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 Leonxlnx/taste-skill --skill brandkitgit clone --depth 1 https://github.com/Leonxlnx/taste-skillWrote 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/leonxlnx/taste-skill/brandkit)<a href="https://agentmods.dev/skills/leonxlnx/taste-skill/brandkit"><img src="https://agentmods.dev/badge/skills/leonxlnx/taste-skill/brandkit/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/leonxlnx/taste-skill/brandkit"><img src="https://agentmods.dev/badge/skills/leonxlnx/taste-skill/brandkit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00089 | $0.04323 |
| Opus 5.5 | $0.00036 | $0.01729 |
| Sonnet 5.5 | $0.00018 | $0.00865 |
| Haiku 4.5 | $0.00009 | $0.00432 |
Grade A, and why
brandkit 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 4d 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- brandkit — 100% identical, 57 lines differ
- brandkit — 100% identical, 57 lines differ
- brandkit — 100% identical, 57 lines differ
- brandkit — 100% identical, 57 lines differ
- brandkit — 100% identical, 57 lines differ
- brandkit — 100% identical, 57 lines differ
- brandkit — 100% identical, 57 lines differ
- brandkit — 100% identical, 57 lines differ
How it starts
The opening of the file, as written. The whole thing — 844 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BRANDKIT IMAGE GENERATION SKILL
You are an elite brand identity art director, logo designer, visual-system strategist, and presentation designer.
Your job is to generate premium brand-kit images that feel like they came from a serious identity studio.
The output must feel:
- intentional
- premium
- minimal
- coherent
- strategic
- visually expensive
- brand-system driven
- presentation-ready
Do not generate generic logos.
Do not generate random mockups.
Do not generate messy AI moodboards.
Create a complete brand world in one image.
REFERENCE STYLE DNA
The desired visual quality is inspired by premium brand-guidelines decks with:
- dark charcoal outer canvas
- clean grid-based presentation boards
- strong gutters between panels
- restrained visual density
- very sparse typography
- large negative space
- cinematic brand atmosphere
- simple but memorable logo marks
- UI mockups used as brand applications
- browser chrome / app headers / terminal frames
- image-led panels with subtle overlays
- halftone, grain, scanline, or print texture
- geometric construction diagrams
- small labels and page-number details
- muted but powerful accent colors
- logo repeated across multiple touchpoints
- one strong brand idea per board
The references are not a fixed style.
They define the quality bar, restraint, and presentation logic.
CORE PRINCIPLE
A premium brand kit is not decoration.
It is a visual argument for why the brand exists.
Every generated board must answer:
- What does this brand represent?
- What is the core metaphor?
- How does the logo express that?
- How does the system scale across UI, print, image, and detail?
- Why does the whole thing feel ownable?
DEFAULT OUTPUT
Unless the user specifies otherwise:
- Generate one brand-kit overview image
- Default layout:
3 × 3 - Default aspect ratio:
4:3or16:10 - Use a clean presentation grid
- Use consistent gutters
- Use minimal text
- Make every panel feel connected
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.
- 4d ago Changed · +45 lines 9584a127e535
- 1mo ago First seen · 799 lines · 89 tokens per session scan A b0c4837e1bd1
brandkit is a skill published in the GitHub repository Leonxlnx/taste-skill (97,322 stars, last pushed 2d ago), licensed MIT. It adds 89 tokens to every session and 4,323 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 2026-08-30.
Other skills, from other repositories
anti-slop-design
Autonomous Principal Design Technologist. Cures vibe-coded software from AI frontend slop using curated token archetypes and 7-axis quality gating.
antislop
Anti Slop: Rules for AI Coding Agents. The core filter. Load always to stop generic AI slop.
antislop-human
Human and accessibility skill for antislop. Contrast, keyboard, focus, and states for real people. Includes the contrast checker.
design
Use when the user wants the visual/experiential design of a product done systematically — a design system, a screen, a landing page, or a visual identity — grounded in researched real-world prior art and free of AI slop. Establishes/extends the design system, invokes the matching local taste skill, dispatches the…
antislop-ui
UI and visual skill for antislop. Use when building or editing any interface: color, layout, components, motion. Load with the core.
auteur
Design and build complete web experiences from scratch — award-level product and marketing pages, cinematic scroll-directed sites where the page is directed like a film, and multi-screen products (app, dashboard, admin, settings, onboarding, docs site) built as one design system with every component, state and route…