html-anything is a local AI-assisted HTML editor in which coding-agent command-line tools create documents such as articles, presentations, posters, prototypes, and reports from reusable templates. People use it to produce HTML and export it to services such as WeChat, X, and Zhihu or to HTML and PNG files. The catalogue entries are the skills and instructions that define its output surfaces and workflows.
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 nexu-io/html-anything --skill saas-landinggit clone --depth 1 https://github.com/nexu-io/html-anythingWrote 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/nexu-io/html-anything/saas-landing)<a href="https://agentmods.dev/skills/nexu-io/html-anything/saas-landing"><img src="https://agentmods.dev/badge/skills/nexu-io/html-anything/saas-landing/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/nexu-io/html-anything/saas-landing"><img src="https://agentmods.dev/badge/skills/nexu-io/html-anything/saas-landing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00024 | $0.00277 |
| Opus 5.5 | $0.00010 | $0.00111 |
| Sonnet 5.5 | $0.00005 | $0.00055 |
| Haiku 4.5 | $0.00002 | $0.00028 |
Grade A, and why
saas-landing scanned grade A with 0 findings 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
【模板: SaaS Landing】 【意图】完整的 SaaS 产品落地页, 把用户内容映射到标准 sections。 【布局】
- Top nav (logo + 导航 + sign-in + 主 CTA)
- Hero (大标题 + 副标 + 双 CTA + 可视化占位)
- Logo wall (社会认证)
- Features (3-6 个特性卡, icon + 标题 + 描述)
- How it works (3 步流程, 数字 + 标题 + 描述)
- Pricing (2-3 档, 推荐档高亮)
- FAQ (details/summary 手风琴)
- Footer 【设计细节】
- 现代 SaaS 风: 大字号, 柔和渐变, glassmorphism 卡片, 滚动入场动画
- 至少处理
md:断点, 移动端单栏
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 First seen · 27 lines · 24 tokens per session scan A ecf14e72f601
saas-landing is a skill published in the GitHub repository nexu-io/html-anything (9,243 stars, last pushed 12d ago), licensed Apache-2.0. It adds 24 tokens to every session and 277 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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