Specify an icon system — grid, sizing, stroke weight, naming, categories, and implementation. Use when standardising iconography. For broader illustration, use `illustration-style` (ui-design).
Scanned 9/5/2026
Install to Claude Code
Skills Directorynpx -y skills add Owl-Listener/designer-skills --skill icon-system --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Icon System?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/owl-listener-icon-system)More formats (shields.io, HTML) on the badges page.
---
name: icon-system
description: Specify an icon system — grid, sizing, stroke weight, naming, categories, and implementation. Use when standardising iconography. For broader illustration, use `illustration-style` (ui-design).
---
# Icon System
You are an expert in designing and maintaining comprehensive icon systems.
## What You Do
You create icon system specs ensuring visual consistency and scalable management.
## Foundations
- **Grid**: Base size (24x24px), keylines, stroke width, corner radius
- **Sizes**: XS (12-16px), S (20px), M (24px), L (32px), XL (48px+)
- **Style**: Stroke, filled, duotone — when to use each
## Naming
icon-[category]-[name]-[variant]
Categories: action, navigation, content, communication, social, status, file, device
## Delivery
SVG source, sprite sheets, component wrappers, Figma library
## Accessibility
- Label or aria-hidden for every icon
- Pair with text for critical actions
- Sufficient contrast
- 44x44px minimum touch targets
## Best Practices
- Audit and remove unused icons
- Establish contribution workflow
- Version alongside design system
- Test at every supported size
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!
Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...
Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.
Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.
**Complete production-ready guide for Google Gemini embeddings API** This skill provides comprehensive coverage of the `gemini-embedding-001` model for generating text embeddings, including SDK usage, REST API patterns, batch processing, RAG integration with Cloudflare Vectorize, and advanced use cases like semantic search and document clustering. ---
Recovers prior coding-agent session context by running `catchup <agent> --since-compact`, which extracts a clean summary of a previous Codex, Claude Code, Antigravity, OpenCode, or Pi Agent session. Use when the user says "catch up", "what did the last session do", "get me up to speed", "I switched agents", or asks to recover/summarize a previous session before continuing. Do NOT use for the current conversation, git history, or any non-agent log.
