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 wangbin3162/agents-skills --skill website-clonergit clone --depth 1 https://github.com/wangbin3162/agents-skillsWrote 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/wangbin3162/agents-skills/website-cloner)<a href="https://agentmods.dev/skills/wangbin3162/agents-skills/website-cloner"><img src="https://agentmods.dev/badge/skills/wangbin3162/agents-skills/website-cloner/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/wangbin3162/agents-skills/website-cloner"><img src="https://agentmods.dev/badge/skills/wangbin3162/agents-skills/website-cloner.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 | $0.00108 | $0.04494 |
| Opus 5.5 | $0.00043 | $0.01798 |
| Sonnet 5.5 | $0.00022 | $0.00899 |
| Haiku 4.5 | $0.00011 | $0.00449 |
Grade A, and why
website-cloner 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 2mo 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.
2. **URL + local reference** — The user has already downloaded a static version (e.g., via browser "Save Page" or `wget`). Use it as a reference to cross-check assets and structure, fill in gaps the live fetch might miss How it starts
The opening of the file, as written. The whole thing — 420 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Website Cloner
You are about to clone a website into a fully self-contained static site — pure HTML, CSS, and JavaScript with zero framework dependencies. The output is a folder of static files that can be opened directly in a browser, served by any static server, or migrated into any framework later.
Interactive Input
If $ARGUMENTS is empty or incomplete, ask the user interactively. Do NOT proceed without the required information. Ask questions one at a time — don't overwhelm with a long form.
Step 1: Target URL
If no URL was provided in $ARGUMENTS, ask:
Q: 要克隆哪个网站?请提供目标 URL。
- Option A: 输入 URL(推荐)— "提供目标网址,例如 https://example.com"
- Option B: 仅本地参考 — "我没有 URL,只有本地已下载的静态文件"
If the user chooses B (no URL), skip to Step 2 but note that extraction will rely entirely on local files — no live fetch possible.
Validate the URL format. If invalid, ask again.
Step 2: Local Reference (Optional)
Ask:
Q: 是否有已下载的静态站点作为参考?
- Option A: 有(推荐)— "提供本地目录路径"
- Option B: 没有 — "直接克隆,无需参考"
If the user provides a path, verify the directory exists. If not, ask again or offer to skip.
Step 3: Output Directory Name
If --dir was not provided in $ARGUMENTS, suggest a default derived from the hostname and ask:
Q: 输出目录叫什么名字?
- 显示建议名称(如
example-com),让用户确认或自定义- 用户可直接回车确认默认值,或输入新名称
If the directory already exists, ask whether to overwrite or pick a new name.
Step 4: Confirm Summary
Before starting, show a summary and ask for confirmation:
即将克隆:
- 目标 URL:
https://example.com- 本地参考:
~/Downloads/example-site(如有)- 输出目录:
./example-com/确认开始?
Only proceed after the user confirms.
Once all inputs are gathered, the workflow proceeds with the collected information.
Input Modes
Based on gathered input, this skill operates in three modes:
- URL only — Fetch the live site, extract everything, rebuild as static files.
- URL + local reference — The user has already downloaded a static version (e.g., via browser "Save Page" or
wget). Use it as a reference to cross-check assets and structure, fill in gaps the live fetch might miss. - Local reference only — No live URL; rebuild from the downloaded files alone.
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.
- 2mo ago First seen · 420 lines · 108 tokens per session scan A 2045c894e94e
website-cloner is a skill published in the GitHub repository wangbin3162/agents-skills (2 stars, last pushed 4mo ago), licensed MIT. It adds 108 tokens to every session and 4,494 once invoked, about $0.0004 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 2026-08-31.
website-cloner compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| website-clonerwangbin3162/agents-skills | Skill | 2 | 4mo ago | MIT | A | 108 | Claude Code |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | today | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 99k | today | Apache-2.0 | A | 19 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 314k | 4d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| chat-pet-sprite-creationmicrosoft/vscode | Skill | 195k | today | MIT | A | 53 | Claude Code, Codex |