kernel-chat-art-direction

A design-planning skill for turning the argument of a Kernel.chat issue into a distinct visual direction. It covers materials, typography, composition, imagery, responsive behavior, and motion.

In plain words
What is it for?
It helps define the editorial sentence, material metaphor, dominant visual gesture, type system, image treatment, layout changes, and motion intent for an issue page.
Why use it?
It gives a page a coherent visual concept before implementation instead of relying on generic styling choices.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/isaacsight/kernel/kernel-chat-art-direction
Any agent
npx skills add isaacsight/kernel --skill kernel-chat-art-direction
Clone the repo
git clone --depth 1 https://github.com/isaacsight/kernel

Made for: Claude Code, Codex.

Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 813 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00065 $0.00813
Opus 5 $0.00032 $0.00407
Sonnet 5 $0.00013 $0.00163
Haiku 4.5 $0.00006 $0.00081

Measured 2d ago against content hash 639aa2d2bda1, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

kernel-chat-art-direction 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 2d 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.

.agents/skills/kernel-chat-art-direction/SKILL.md · 57 lines

How it starts

The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Kernel.chat Art Direction

Purpose

Turn an editorial argument into a recognizable visual world before writing page code. Make every choice carry meaning: material, type, scale, image treatment, negative space, rhythm, and motion.

Use $kernel-chat-web-design after this skill to implement the direction in the house system. Use $motion-design when the direction calls for substantial choreography. Use $kernel-chat-design-qa after implementation.

Start With the Editorial Sentence

Write one sentence in this form:

This issue argues that [claim], so the page should feel like [material place or process], moving from [opening state] to [closing state].

Do not select a visual style until this sentence is specific. Reject adjectives that do not imply a design decision, such as premium, modern, clean, or immersive.

Build the Direction

  1. Choose one material metaphor. Examples: an annotated field notebook, a night train timetable, a conservation ledger, a translucent laboratory sleeve. Define its paper, ink, edge, mark, and light behavior.
  2. Name the dominant gesture. Give the composition one memorable act: an interrupted column, a vertical specimen rail, a horizon that shifts between spreads, or a full-bleed plate cut by marginal evidence.
  3. Set the type hierarchy. Define display voice, reading voice, metadata voice, bilingual relationship, line length, and at least one intentional scale collision. Preserve kernel.chat's house type families unless the repository explicitly supports another licensed face.
  4. Design the cover as an argument. The cover must communicate issue identity at thumbnail size and reward close reading. Use one focal relationship, not a collage of every idea.
  5. Create one media grammar. Specify palette, crop logic, camera distance, texture, grain, illustration method, and what may repeat. Original assets may vary in composition while sharing the same material rules.
  6. Compose a rhythm, not a component stack. Alternate compression and release, image and text, evidence and reflection. Avoid repeated equal rectangles, uniform section padding, and one-card-per-idea layouts.
  7. Recompose for small screens. State what becomes the mobile anchor, what moves into the reading flow, what loses ornament, and what remains interactive. Mobile is a new composition, not a squeezed desktop.
  8. Write the motion intent. Name what moves, why it moves, its physical analogy, and its resting state. Do not prescribe decorative motion with no editorial role.

Read the full file on GitHub · 57 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 2d ago First seen · 57 lines · 65 tokens per session scan A 639aa2d2bda1

Subscribe to this mod's changes

kernel-chat-art-direction is a skill published in the GitHub repository isaacsight/kernel (16 stars, last pushed 3d ago), licensed MIT. It adds 65 tokens to every session and 813 once invoked, about $0.0003 per session on Opus 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.

Related

Other skills, from other repositories

agent-reach

MUST USE when user wants to 调研/research/搜索/search/查/找/look up anything on the internet — e.g. 全网调研 X / 帮我调研一下 X / 查一下 X / 搜搜 X / 看看大家怎么评价 X / X 上有什么讨论 / research this topic。 Also MUST USE when user mentions any platform or shares any URL/链接: 小红书/xiaohongshu/xhs, Twitter/推特/X, B站/bilibili, Reddit, Facebook, Instagram…

Panniantong/Agent-Reach · 349 tokens

add-backend

Guide for adding a backend (Rust or Python) to the agent-sec-core security middleware. Use when creating new backends, integrating Rust or Python code into the security middleware, or extending with new backend actions.

alibaba/anolisa · 46 tokens

skill-ledger

Skill 安全状态查看、风险暴露审查、用户决策、快速扫描认证与可选深度扫描。支持用户主动查看或扫描单个/全部 Skill;当用户要求 agent 安装 Skill 且安装成功后,必须自动对最终本地目录执行快速扫描认证。.

alibaba/anolisa · 67 tokens

regex-mastery

Use this skill when writing regular expressions, debugging pattern matching,optimizing regex performance, or implementing text validation. Triggers on regex, regular expressions, pattern matching, lookahead, lookbehind, named groups, capture groups, backreferences, and any task requiring text pattern matching.

alibaba/anolisa · 60 tokens

install-openclaw

Install and configure OpenClaw non-interactively with Alibaba Cloud Model Studio. Use when the user asks to install OpenClaw, configure Aliyun Bailian/Model Studio/DashScope credentials, choose pay-as-you-go, Coding Plan, or Token Plan billing, set Base URL/model config, optionally configure DingTalk, start the local…

alibaba/anolisa · 85 tokens

bernstein-plan

Create and manage multi-step execution plans in Bernstein. Plans decompose complex goals into stages with dependencies. Use when the user wants to plan a complex feature, break down a large task, or review an execution plan before agents start working.

sipyourdrink-ltd/bernstein · 51 tokens