Local AI App Integration
amd/skills
Integrates local AI capabilities into applications using Embeddable Lemonade.
Cloudflare Workers AI for serverless GPU inference. An agent skill from secondsky/claude-skills.
Install Cloudflare Workers AI
$ npx skills add secondsky/claude-skills --skill cloudflare-workers-ai -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install secondsky/claude-skills cloudflare-workers-ai --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/secondsky/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/cloudflare-workers-ai/skills/cloudflare-workers-ai .claude/skills/cloudflare-workers-ai && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "cloudflare-workers-ai" agent skill from https://github.com/secondsky/claude-skills/tree/main/plugins/cloudflare-workers-ai/skills/cloudflare-workers-ai into .claude/skills/cloudflare-workers-ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloudflare-workers-ai", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/secondsky/claude-skills/tree/main/plugins/cloudflare-workers-ai/skills/cloudflare-workers-aiType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add secondsky/claude-skills --skill cloudflare-workers-ai -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install secondsky/claude-skills cloudflare-workers-ai --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/secondsky/claude-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/cloudflare-workers-ai/skills/cloudflare-workers-ai .agents/skills/cloudflare-workers-ai && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "cloudflare-workers-ai" agent skill from https://github.com/secondsky/claude-skills/tree/main/plugins/cloudflare-workers-ai/skills/cloudflare-workers-ai into .agents/skills/cloudflare-workers-ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloudflare-workers-ai", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add secondsky/claude-skills --skill cloudflare-workers-ai -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install secondsky/claude-skills cloudflare-workers-ai --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/secondsky/claude-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/cloudflare-workers-ai/skills/cloudflare-workers-ai .cursor/skills/cloudflare-workers-ai && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "cloudflare-workers-ai" agent skill from https://github.com/secondsky/claude-skills/tree/main/plugins/cloudflare-workers-ai/skills/cloudflare-workers-ai into .cursor/skills/cloudflare-workers-ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloudflare-workers-ai", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/secondsky/claude-skills.git --path plugins/cloudflare-workers-ai/skills/cloudflare-workers-ai--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add secondsky/claude-skills --skill cloudflare-workers-ai -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install secondsky/claude-skills cloudflare-workers-ai --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/secondsky/claude-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/cloudflare-workers-ai/skills/cloudflare-workers-ai .gemini/skills/cloudflare-workers-ai && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "cloudflare-workers-ai" agent skill from https://github.com/secondsky/claude-skills/tree/main/plugins/cloudflare-workers-ai/skills/cloudflare-workers-ai into .gemini/skills/cloudflare-workers-ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloudflare-workers-ai", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install secondsky/claude-skills cloudflare-workers-aiInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add secondsky/claude-skills --skill cloudflare-workers-ai -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/secondsky/claude-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/cloudflare-workers-ai/skills/cloudflare-workers-ai .github/skills/cloudflare-workers-ai && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "cloudflare-workers-ai" agent skill from https://github.com/secondsky/claude-skills/tree/main/plugins/cloudflare-workers-ai/skills/cloudflare-workers-ai into .github/skills/cloudflare-workers-ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloudflare-workers-ai", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add secondsky/claude-skills --skill cloudflare-workers-ai -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install secondsky/claude-skills cloudflare-workers-ai --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/secondsky/claude-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/cloudflare-workers-ai/skills/cloudflare-workers-ai .opencode/skills/cloudflare-workers-ai && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "cloudflare-workers-ai" agent skill from https://github.com/secondsky/claude-skills/tree/main/plugins/cloudflare-workers-ai/skills/cloudflare-workers-ai into .opencode/skills/cloudflare-workers-ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloudflare-workers-ai", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
cloudflare-workers-ai- GitHub stars
- 227
- Token cost
- ~2.4k tokens
- SKILL.md length
- 594 words
- Files
- 10 (incl. references)
- Skills in repo
- 169
- Repo updated
- First seen
- Licence
- MIT
At a glance
Cloudflare Workers AI for serverless GPU inference. An agent skill from secondsky/claude-skills.
- Works in 3 steps: Add AI Binding → Run Your First Model → Add Streaming (Recommended)
- Text/image generation
- SKILL.md covers Table of Contents, Quick Start (5 minutes), Workers AI API Reference and Model Selection Guide, plus 8 more sections
- Runs TypeScript scripts from its folder; reaches api.cloudflare.com; needs CLOUDFLARE_API_KEY
What it does
Cloudflare Workers AI is an agent skill from secondsky/claude-skills. Cloudflare Workers AI for serverless GPU inference. Use for LLMs, text/image generation, embeddings, or encountering AIERROR, rate limits, token exceeded errors.
Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files, including reference files (for example `references/best-practices.md`, `references/integrations.md` and `references/models-catalog.md`).
It sits in AI & LLM Engineering, covering Rate limiting, Embeddings and Image generation. It works with Workers AI and Cloudflare Workers. The repository describes itself as: Production-ready skills for Claude Code CLI - Cloudflare, React, Tailwind v4, and AI integrations. The licence is MIT.
When your agent uses it
- Text/image generation
- Encountering AIERROR
- Token exceeded errors
Example prompts
- “/cloudflare-workers-ai”
Requirements
- Node.js
- A credential in CLOUDFLARE_API_KEY
Workflow steps
3 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 8837836. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships script files (TypeScript), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
api.cloudflare.com
Also links to:
developers.cloudflare.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
CLOUDFLARE_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Cloudflare Workers AI loads about 2.4k tokens when it runs, and up to ~8.6k if it reads all its reference files. Until then it costs about 46 tokens; SKILL.md has 594 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from secondsky/claude-skills at commit 8837836, republished under its MIT licence (© secondsky). 594 words, ~2,441 tokens.
Download SKILL.mdSave it as
.claude/skills/cloudflare-workers-ai/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.- name
- cloudflare-workers-ai
- description
- Cloudflare Workers AI for serverless GPU inference. Use for LLMs, text/image generation, embeddings, or encountering AI_ERROR, rate limits, token exceeded errors.
- metadata.keywords
- workers ai, cloudflare ai, ai bindings, llm workers, @cf/meta/llama, workers ai models, ai inference, cloudflare llm, ai streaming, text generation ai, ai…
- license
- MIT
Cloudflare Workers AI - Complete Reference
Production-ready knowledge domain for building AI-powered applications with Cloudflare Workers AI.
Status: Production Ready ✅ Last Updated: 2025-11-21 Dependencies: cloudflare-worker-base (for Worker setup) Latest Versions: wrangler@4.81.0, @cloudflare/workers-types@4.20260408.0
Table of Contents
- Quick Start (5 minutes)
- Workers AI API Reference
- Model Selection Guide
- Common Patterns
- AI Gateway Integration
- Rate Limits & Pricing
- Production Checklist
Quick Start (5 minutes)
1. Add AI Binding
wrangler.jsonc:
{
"ai": {
"binding": "AI"
}
}2. Run Your First Model
export interface Env {
AI: Ai;
}
export default {
async fetch(request: Request, env: Env): Promise<Response> {
const response = await env.AI.run('@cf/meta/llama-3.1-8b-instruct', {
prompt: 'What is Cloudflare?',
});
return Response.json(response);
},
};3. Add Streaming (Recommended)
const stream = await env.AI.run('@cf/meta/llama-3.1-8b-instruct', {
messages: [{ role: 'user', content: 'Tell me a story' }],
stream: true, // Always use streaming for text generation!
});
return new Response(stream, {
headers: { 'content-type': 'text/event-stream' },
});Why streaming?
- Prevents buffering large responses in memory
- Faster time-to-first-token
- Better user experience for long-form content
- Avoids Worker timeout issues
Workers AI API Reference
Core API: env.AI.run()
const response = await env.AI.run(model, inputs, options?);| Parameter | Type | Description |
|---|---|---|
model | string | Model ID (e.g., @cf/meta/llama-3.1-8b-instruct) |
inputs | object | Model-specific inputs (see model type below) |
options.gateway.id | string | AI Gateway ID for caching/logging |
options.gateway.skipCache | boolean | Skip AI Gateway cache |
Returns: Promise<ModelOutput> (non-streaming) or ReadableStream (streaming)
Input Types by Model Category
| Category | Key Inputs | Output |
|---|---|---|
| Text Generation | messages[], stream, max_tokens, temperature | { response: string } |
| Embeddings | text: string | string[] | { data: number[][], shape: number[] } |
| Image Generation | prompt, num_steps, guidance | Binary PNG |
| Vision | messages[].content[].image_url | { response: string } |
📄 Full model details: Load references/models-catalog.md for complete model list, parameters, and rate limits.
Model Selection Guide
Text Generation (LLMs)
| Model | Best For | Rate Limit | Size |
|---|---|---|---|
@cf/meta/llama-3.1-8b-instruct | General purpose, fast | 300/min | 8B |
@cf/meta/llama-3.2-1b-instruct | Ultra-fast, simple tasks | 300/min | 1B |
@cf/qwen/qwen1.5-14b-chat-awq | High quality, complex reasoning | 150/min | 14B |
@cf/deepseek-ai/deepseek-r1-distill-qwen-32b | Coding, technical content | 300/min | 32B |
@hf/thebloke/mistral-7b-instruct-v0.1-awq | Fast, efficient | 400/min | 7B |
Text Embeddings
| Model | Dimensions | Best For | Rate Limit |
|---|---|---|---|
@cf/baai/bge-base-en-v1.5 | 768 | General purpose RAG | 3000/min |
@cf/baai/bge-large-en-v1.5 | 1024 | High accuracy search | 1500/min |
@cf/baai/bge-small-en-v1.5 | 384 | Fast, low storage | 3000/min |
Image Generation
| Model | Best For | Rate Limit | Speed |
|---|---|---|---|
@cf/black-forest-labs/flux-1-schnell | High quality, photorealistic | 720/min | Fast |
@cf/stabilityai/stable-diffusion-xl-base-1.0 | General purpose | 720/min | Medium |
@cf/lykon/dreamshaper-8-lcm | Artistic, stylized | 720/min | Fast |
Vision Models
| Model | Best For | Rate Limit |
|---|---|---|
@cf/meta/llama-3.2-11b-vision-instruct | Image understanding | 720/min |
@cf/unum/uform-gen2-qwen-500m | Fast image captioning | 720/min |
Common Patterns
Pattern 1: Chat with Streaming
app.post('/chat', async (c) => {
const { messages } = await c.req.json<{ messages: Array<{ role: string; content: string }> }>();
const stream = await c.env.AI.run('@cf/meta/llama-3.1-8b-instruct', { messages, stream: true });
return new Response(stream, { headers: { 'content-type': 'text/event-stream' } });
});Pattern 2: RAG (Retrieval Augmented Generation)
// 1. Generate embedding for query
const embeddings = await env.AI.run('@cf/baai/bge-base-en-v1.5', { text: [userQuery] });
// 2. Search Vectorize
const matches = await env.VECTORIZE.query(embeddings.data[0], { topK: 3 });
// 3. Build context
const context = matches.matches.map((m) => m.metadata.text).join('\n\n');
// 4. Generate with context
const stream = await env.AI.run('@cf/meta/llama-3.1-8b-instruct', {
messages: [
{ role: 'system', content: `Answer using this context:\n${context}` },
{ role: 'user', content: userQuery },
],
stream: true,
});
return new Response(stream, { headers: { 'content-type': 'text/event-stream' } });📄 More patterns: Load references/best-practices.md for structured output, image generation, multi-model consensus, and production patterns.
AI Gateway Integration
Enable caching, logging, and cost tracking with AI Gateway:
const response = await env.AI.run('@cf/meta/llama-3.1-8b-instruct', { prompt: 'Hello' }, {
gateway: { id: 'my-gateway', skipCache: false },
});Benefits: Cost tracking, response caching (50-90% savings on repeated queries), request logging, rate limiting, analytics.
Show full SKILL.md (240 more words)Show less
Rate Limits & Pricing
Information last verified: 2025-01-14
Rate limits and pricing vary significantly by model. Always check the official documentation for the most current information:
- Rate Limits: https://developers.cloudflare.com/workers-ai/platform/limits/
- Pricing: https://developers.cloudflare.com/workers-ai/platform/pricing/
Free Tier: 10,000 neurons/day Paid Tier: $0.011 per 1,000 neurons
📄 Per-model details: See references/models-catalog.md for specific rate limits and pricing for each model.
Production Checklist
Essential before deploying:
- Enable AI Gateway for cost tracking
- Implement streaming for text generation
- Add rate limit retry with exponential backoff
- Validate input length (prevent token limit errors)
- Add input sanitization (prevent prompt injection)
📄 Full checklist: Load references/best-practices.md for complete production checklist, error handling patterns, monitoring, and cost optimization.
External SDK Integrations
Workers AI supports OpenAI SDK compatibility and Vercel AI SDK:
// OpenAI SDK - use same patterns with Workers AI models
const openai = new OpenAI({
apiKey: env.CLOUDFLARE_API_KEY,
baseURL: `https://api.cloudflare.com/client/v4/accounts/${env.CLOUDFLARE_ACCOUNT_ID}/ai/v1`,
});
// Vercel AI SDK - native integration
import { createWorkersAI } from 'workers-ai-provider';
const workersai = createWorkersAI({ binding: env.AI });📄 Full integration guide: Load references/integrations.md for OpenAI SDK, Vercel AI SDK, and REST API examples.
Limits Summary
| Feature | Limit |
|---|---|
| Concurrent requests | No hard limit (rate limits apply) |
| Max input tokens | Varies by model (typically 2K-128K) |
| Max output tokens | Varies by model (typically 512-2048) |
| Streaming chunk size | ~1 KB |
| Image size (output) | ~5 MB |
| Request timeout | Workers timeout applies (30s default, 5m max CPU) |
| Daily free neurons | 10,000 |
| Rate limits | See "Rate Limits & Pricing" section |
When to Load References
| Reference File | Load When... |
|---|---|
references/models-catalog.md | Choosing a model, checking rate limits, comparing model capabilities |
references/best-practices.md | Production deployment, error handling, cost optimization, security |
references/integrations.md | Using OpenAI SDK, Vercel AI SDK, or REST API instead of native binding |
References
© secondsky, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 9 other files (references) in plugins/cloudflare-workers-ai/skills/cloudflare-workers-ai of secondsky/claude-skills.
- SKILL.md
- references/best-practices.md
- references/integrations.md
- references/models-catalog.md
- templates/ai-embeddings-rag.ts
- templates/ai-gateway-integration.ts
- templates/ai-image-generation.ts
- templates/ai-text-generation.ts
- templates/ai-vision-models.ts
- templates/wrangler-ai-config.jsonc
Open the folder on GitHubat commit 8837836
Compare with similar skills
Cloudflare Workers AI next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Cloudflare Workers AI this skillsecondsky/claude-skills | 227 | — | ~2.4k | Automated safety check: Pass | MIT | |
| Local AI App Integrationamd/skills | 395 | — | ~6k | Automated safety check: Pass | MIT | |
| Openai APIynulihao/AgentSkillOS | 617 | 1 repos | ~5.9k | Automated safety check: Notes | None | |
| Apikerhodgef/apiker | 127 | — | ~1.4k | Automated safety check: Pass | MIT | |
| Upstash Redisgithub/awesome-copilot | 40k | — | ~1.7k | Automated safety check: Pass | MIT | |
| Cloudflare Worker Devcuriositech/some_claude_skills | 243 | — | ~3.4k | Automated safety check: Notes | MIT |
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Questions about Cloudflare Workers AI
What does Cloudflare Workers AI do?
Cloudflare Workers AI for serverless GPU inference. An agent skill from secondsky/claude-skills. Cloudflare Workers AI is an agent skill from secondsky/claude-skills. Cloudflare Workers AI for serverless GPU inference.
When should I use Cloudflare Workers AI?
Cloudflare Workers AI fits situations like: text/image generation; encountering AIERROR; token exceeded errors.
How do I install Cloudflare Workers AI in Claude Code?
Run `npx skills add secondsky/claude-skills --skill cloudflare-workers-ai -a claude-code`. Or copy the skill folder (plugins/cloudflare-workers-ai/skills/cloudflare-workers-ai in secondsky/claude-skills) into .claude/skills/cloudflare-workers-ai in your project. Claude Code loads it when a task matches its description.
How do I install Cloudflare Workers AI in Codex?
Run `npx skills add secondsky/claude-skills --skill cloudflare-workers-ai -a codex`. Or copy the skill folder (plugins/cloudflare-workers-ai/skills/cloudflare-workers-ai in secondsky/claude-skills) into .agents/skills/cloudflare-workers-ai in your project. Codex loads it when a task matches its description.
Can I use Cloudflare Workers AI in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add secondsky/claude-skills --skill cloudflare-workers-ai -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cloudflare-workers-ai, .gemini/skills/cloudflare-workers-ai, .github/skills/cloudflare-workers-ai and .opencode/skills/cloudflare-workers-ai in your project.
What does Cloudflare Workers AI need to run?
Going by SKILL.md and its folder, Cloudflare Workers AI needs TypeScript for the scripts in its folder and credentials named CLOUDFLARE_API_KEY. Our summary lists: Node.js; A credential in CLOUDFLARE_API_KEY.
Does Cloudflare Workers AI access the network?
SKILL.md names 2 domains. In commands or code: api.cloudflare.com; the agent is likely to contact it when it follows the instructions. As links in the text: developers.cloudflare.com. This is read from the text; nothing was executed.
Is Cloudflare Workers AI safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Cloudflare Workers AI use?
Cloudflare Workers AI is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Cloudflare Workers AI use?
About 2.4k tokens (SKILL.md is roughly 9.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 6.2k tokens, read only when the agent opens those files.
What are the alternatives to Cloudflare Workers AI?
Skills that share tags, products or a category with Cloudflare Workers AI: Local AI App Integration (amd/skills, 395 stars), Openai API (ynulihao/AgentSkillOS, 617 stars), Apiker (hodgef/apiker, 127 stars) and Upstash Redis (github/awesome-copilot, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Cloudflare Workers AI?
secondsky (a GitHub user) maintains it in secondsky/claude-skills, which has 227 GitHub stars. The repository holds 169 skills in this directory. The repository was last updated on September 28, 2026.
Source: secondsky/claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.