llm-icon-finder

daymade/claude-code-skills · updated Apr 8, 2026

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$npx skills add https://github.com/daymade/claude-code-skills --skill llm-icon-finder
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summary

Access AI/LLM model brand icons and logos from the lobe-icons library. The library contains 100+ icons for models (Claude, GPT, Gemini), providers (OpenAI, Anthropic, Google), and applications (ComfyUI, LobeChat).

skill.md

Finding AI/LLM Brand Icons

Access AI/LLM model brand icons and logos from the lobe-icons library. The library contains 100+ icons for models (Claude, GPT, Gemini), providers (OpenAI, Anthropic, Google), and applications (ComfyUI, LobeChat).

Icon Formats and Variants

Available formats: SVG (scalable), PNG (raster), WEBP (compressed) Theme variants: light, dark, and color (some icons)

CDN URL Patterns

Construct URLs using these patterns:

# SVG
https://raw.githubusercontent.com/lobehub/lobe-icons/refs/heads/master/packages/static-svg/{light|dark}/{icon-name}.svg

# PNG
https://raw.githubusercontent.com/lobehub/lobe-icons/refs/heads/master/packages/static-png/{light|dark}/{icon-name}.png

# WEBP
https://raw.githubusercontent.com/lobehub/lobe-icons/refs/heads/master/packages/static-webp/{light|dark}/{icon-name}.webp

# Color variant (append -color to icon-name)
https://raw.githubusercontent.com/lobehub/lobe-icons/refs/heads/master/packages/static-png/dark/{icon-name}-color.png

Icon naming convention: Lowercase, hyphenated (e.g., claude, chatglm, openai, huggingface)

Workflow

When users request icons:

  1. Identify icon name (usually lowercase company/model name, hyphenated if multi-word)
  2. Determine format (default: PNG) and theme (default: dark)
  3. Construct CDN URL using pattern above
  4. Provide URL to user
  5. If download requested, use Bash tool with curl
  6. Include web viewer link: https://lobehub.com/icons/{icon-name}

Finding Icon Names

Common icons: See references/icons-list.md for comprehensive list organized by category (Models, Providers, Applications, Chinese AI)

Uncertain names:

  • Browse https://lobehub.com/icons
  • Try variations (e.g., company name vs product name: alibaba vs alibabacloud)
  • Check for -color variants if standard URL fails

Chinese AI models: Support Chinese queries (e.g., "智谱" → chatglm, "月之暗面" → moonshot)

Examples

Single icon request:

User: "Claude icon"
→ Provide: https://raw.githubusercontent.com/lobehub/lobe-icons/refs/heads/master/packages/static-png/dark/claude.png
→ Also mention color variant and web viewer link

Multiple icons download:

curl -o openai.svg "https://raw.githubusercontent.com/lobehub/lobe-icons/.../dark/openai.svg"
curl -o anthropic.svg "https://raw.githubusercontent.com/lobehub/lobe-icons/.../dark/anthropic.svg"

Chinese query:

User: "找一下智谱的图标"
→ Identify: 智谱 = ChatGLM → icon name: chatglm
→ Provide URLs and mention related icons (zhipu, codegeex)

Troubleshooting

If URL returns 404:

  1. Try -color suffix variant
  2. Check alternate naming (e.g., chatgpt vs gpt, google vs gemini)
  3. Direct user to https://lobehub.com/icons to browse
  4. Search repository: https://github.com/lobehub/lobe-icons

Reference Files

  • references/icons-list.md - Comprehensive list of 100+ available icons by category
  • references/developer-info.md - npm installation and React usage examples
how to use llm-icon-finder

How to use llm-icon-finder on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add llm-icon-finder
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/daymade/claude-code-skills --skill llm-icon-finder

The skills CLI fetches llm-icon-finder from GitHub repository daymade/claude-code-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/llm-icon-finder

Reload or restart Cursor to activate llm-icon-finder. Access the skill through slash commands (e.g., /llm-icon-finder) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.765 reviews
  • Valentina Mensah· Dec 28, 2024

    llm-icon-finder reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Valentina Gonzalez· Dec 20, 2024

    Useful defaults in llm-icon-finder — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Ama Thomas· Dec 8, 2024

    llm-icon-finder is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Noah Johnson· Dec 8, 2024

    llm-icon-finder has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Shikha Mishra· Dec 4, 2024

    Keeps context tight: llm-icon-finder is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Ganesh Mohane· Dec 4, 2024

    Useful defaults in llm-icon-finder — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Benjamin Huang· Dec 4, 2024

    I recommend llm-icon-finder for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Benjamin Kim· Dec 4, 2024

    Registry listing for llm-icon-finder matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Aisha Reddy· Nov 27, 2024

    llm-icon-finder reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Mia Sharma· Nov 27, 2024

    llm-icon-finder fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

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