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.
npx skills add weiyi88/cc-code --skill deploy-cfgit clone --depth 1 https://github.com/weiyi88/cc-codeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/weiyi88/cc-code/deploy-cf)<a href="https://agentmods.dev/skills/weiyi88/cc-code/deploy-cf"><img src="https://agentmods.dev/badge/skills/weiyi88/cc-code/deploy-cf/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/weiyi88/cc-code/deploy-cf"><img src="https://agentmods.dev/badge/skills/weiyi88/cc-code/deploy-cf.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00016 | $0.03216 |
| Opus 5.5 | $0.00006 | $0.01286 |
| Sonnet 5.5 | $0.00003 | $0.00643 |
| Haiku 4.5 | $0.00002 | $0.00322 |
Grade A, and why
deploy-cf scanned grade A with 1 finding 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 1mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s -o /dev/null -w "HTTP %{http_code}" "https://<project-name>.pages.dev" How it starts
The opening of the file, as written. The whole thing — 395 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cloudflare Pages 上线技能
将 Next.js (App Router) 项目部署到 Cloudflare Pages Edge Runtime,包含完整的预检、构建、部署、域名配置流程。
适用场景
- Next.js App Router 项目部署到 Cloudflare Pages
- 已有 GitHub 仓库,需要上线到 Cloudflare
- 需要为 Cloudflare Pages 配置自定义域名
完整流程
Phase 0: 预检(必做)
部署前必须检查以下项目配置,逐项修复:
0.1 wrangler.toml
确认项目根目录存在 wrangler.toml,内容必须包含:
#:schema node_modules/wrangler/config-schema.json
name = "<project-name>"
compatibility_date = "2024-12-01"
compatibility_flags = ["nodejs_compat"]
pages_build_output_dir = ".vercel/output/static"
name:项目名(小写,将作为<name>.pages.dev子域名)compatibility_flags:必须包含nodejs_compat,否则运行时 503 错误pages_build_output_dir:必须设置,否则 wrangler 不会应用 compatibility_flags
0.2 next.config.mjs
/** @type {import('next').NextConfig} */
const nextConfig = {
reactStrictMode: true,
images: {
unoptimized: true, // Cloudflare Pages 不支持 Next.js 图片优化
},
// 注意:不要设置 output: 'export',@cloudflare/next-on-pages 会处理输出格式
};
export default nextConfig;
0.3 Edge Runtime 声明
所有动态页面和 API 路由必须添加 Edge Runtime 声明:
// app/page.tsx
export const runtime = 'edge';
// app/api/xxx/route.ts
export const runtime = 'edge';
// app/generator/[param]/page.tsx
export const runtime = 'edge';
⚠️ 关键限制(Next.js 15):
export const runtime = 'edge'和generateStaticParams不能共存- 选择 edge runtime 就必须是动态渲染,放弃静态生成
params类型变为Promise<{...}>,需要await params
// Next.js 15 正确写法
export default async function Page({
params,
}: {
params: Promise<{ platform: string }>;
}) {
const { platform } = await params;
// ...
}
0.4 依赖版本兼容
| 依赖 | 要求 | 原因 |
|---|---|---|
next |
>= 14.3.0 | @cloudflare/next-on-pages 最低要求 |
@cloudflare/next-on-pages |
最新版 | 构建适配器 |
eslint + eslint-config-next |
版本匹配 | ESLint v9 与 eslint-config-next 不兼容,用 v8 |
# 安装必要依赖
npm install -D @cloudflare/next-on-pages
# 如有 ESLint 冲突
npm install -D eslint@8 eslint-config-next@14
What ships with it
1 file 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.
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.
- 1mo ago Changed · -31 tokens per session b67e1fb7a070
- 1mo ago First seen · 395 lines · 47 tokens per session scan A b8139afe3bcb
deploy-cf is a skill published in the GitHub repository weiyi88/cc-code (5 stars, last pushed yesterday), licensed MIT. It adds 16 tokens to every session and 3,216 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-13.
Other skills, from other repositories
flow-nexus-swarm
Cloud-based AI swarm deployment and event-driven workflow automation with Flow Nexus platform.
infrastructure
A guide for cloud-native infrastructure: software and configuration used to run applications in containers and manage cloud resources. It covers Kubernetes, Helm, Kustomize, GitOps tools such as ArgoCD and Flux, and infrastructure-as-code tools such as Terraform and Pulumi.
remote-compute-modal
Run GPU jobs on the user's own Modal account via host.compute.create('byoc:modal', ...). Covers the create→submit→waitfornotification flow, the computeprovider kernel for env setup, image/volume resolution, and the two approval cards. Load once you've decided to dispatch to Modal.
compute-env-setup
Set up a compute environment on a remote provider so Claude Science jobs can run there. Covers direct SSH/conda hosts, Slurm clusters, container-via-bridge runners, and managed-API providers (Modal, GCP, RunPod). Use when standing up a new provider, porting an env to a different backend, adding a tool that needs its…
managed-model-endpoints
Register a model service in the managed family — a local model server container the daemon starts/stops on demand, or a remote upstream model API (https). Read the runbook, allocate a port (local only), compose idempotent start/stop scripts (local only), register once. Load when the user wants a model service…
vs-project
Create Viking web projects, start and verify a local preview, or deploy a generated project to Volcengine IGA Pages when explicitly requested. Includes agent-guided feature, eligible application, dataset, scene, and authentication choices. Use only after confirming the installed CLI exposes vs project; otherwise stop…