By mikitahimpel
Opinionated design taste skill plus two subagents that apply it. The designer skill defines aesthetic principles and anti-patterns; design-reviewer critiques existing UI from screenshots; design-builder implements new UI from spec. Stack-agnostic.
Builds new UI — components, pages, or full screens — with an opinionated aesthetic instead of generic defaults. Use when the user asks to design or build a UI from scratch, redesign an existing surface, or produce a fresh aesthetic direction. Returns implementation in the project's existing stack.
Critiques an existing UI from screenshots, URLs, or live screens. Returns prioritized, actionable findings without editing code. Use when the user asks for a design review, second opinion, screenshot critique, or "is this good?" question on visual work.
Personal skills and agents for Claude Code, Codex, and OpenCode.
designerOpinionated design taste skill plus two subagents that apply it.
designer skill — stack-agnostic aesthetic principles and anti-patterns. Single source of truth for what "good" looks like.design-reviewer agent — critiques existing UI from screenshots. Read-only; returns prioritized findings tied to principles in the skill.design-builder agent — implements new UI from spec. Commits to one aesthetic direction before writing code.comment-disciplineRules for writing source-code comments that serve future readers — not the conversation that produced the code.
Prevents the common AI-coding failure where agents add comments like "switched to library X as you suggested" or "refactored from earlier approach" — comments that document the chat, not the code, and become noise to any future reader who only has the file in front of them.
Use this when the plugin makes sense across all your projects.
/plugin marketplace add mikitahimpel/ai-toolkit
/plugin install designer@ai-toolkit
/plugin install comment-discipline@ai-toolkit
After install, skills are available as /designer:designer and /comment-discipline:comment-discipline. Agents from the designer plugin appear in /agents.
/plugins
Then add this repo as a plugin source and install the plugins. Codex installs the skill components only — agents are Claude-specific and live in ~/.codex/AGENTS.md as a different format.
If you've already installed the Claude plugin above, no separate install is needed. OpenCode scans ~/.claude/skills/ natively, so both skills are discovered automatically.
If you don't use Claude Code, drop a copy of each skill folder into ~/.config/opencode/skills/<name>/ manually.
Use this when a specific repo should ship with these plugins so anyone who clones it gets the same setup.
In the project's .claude/settings.json (commit this to the repo):
{
"extraKnownMarketplaces": {
"ai-toolkit": {
"type": "github",
"repo": "mikitahimpel/ai-toolkit"
}
},
"enabledPlugins": {
"designer@ai-toolkit": true,
"comment-discipline@ai-toolkit": true
}
}
Anyone opening the project in Claude Code is prompted to trust the marketplace on first run, then the plugins auto-install for that project. The plugins are scoped to the project — they do not become globally enabled.
Project-level install in Codex is configured via .codex/config.toml at the project root. Codex's plugin scoping is still evolving; check the Codex docs for the current syntax. The skills can also be dropped directly into the project's .codex/skills/ directory as a no-config fallback.
OpenCode reads project-level skills from .opencode/skills/ and .claude/skills/ at the project root. Either drop the skill folders there directly, or declare the dependency in opencode.json.
ai-toolkit/
├── .claude-plugin/
│ └── marketplace.json
└── plugins/
├── designer/
│ ├── .claude-plugin/plugin.json
│ ├── .codex-plugin/plugin.json
│ ├── skills/designer/SKILL.md
│ └── agents/
│ ├── design-reviewer.md
│ └── design-builder.md
└── comment-discipline/
├── .claude-plugin/plugin.json
├── .codex-plugin/plugin.json
└── skills/comment-discipline/SKILL.md
MIT
Uses power tools
Uses Bash, Write, or Edit tools
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npx claudepluginhub mikitahimpel/ai-toolkit --plugin designerRules for writing source-code comments that serve future readers, not the conversation that produced the code. Prevents the common AI-coding failure mode where agents add comments documenting chat history instead of documenting code.
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