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 malue-ai/dazee-small --skill video-script-writergit clone --depth 1 https://github.com/malue-ai/dazee-smallWrote 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/malue-ai/dazee-small/video-script-writer)<a href="https://agentmods.dev/skills/malue-ai/dazee-small/video-script-writer"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/video-script-writer/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/malue-ai/dazee-small/video-script-writer"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/video-script-writer.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 | $0.00034 | $0.00752 |
| Opus 5 | $0.00017 | $0.00376 |
| Sonnet 5 | $0.00007 | $0.00150 |
| Haiku 4.5 | $0.00003 | $0.00075 |
Grade A, and why
video-script-writer 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 9d 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
视频脚本创作
帮助用户创作各类视频脚本：短视频口播、YouTube 长视频、教学视频、产品演示。
使用场景
- 用户说「帮我写一个 3 分钟的产品介绍视频脚本」
- 用户说「写个短视频口播文案」「TikTok 脚本」
- 用户说「做一个教学视频的分镜脚本」
- 用户说「帮我写视频字幕稿」
支持的视频类型
短视频口播（TikTok / Reels / 短视频）
时长: 15-60 秒
结构:
1. Hook（前 3 秒抓住注意力）
2. 核心观点（1 个重点）
3. 例子或证据
4. CTA（关注/点赞/评论引导）
格式:
[00:00-00:03] Hook: ...
[00:03-00:15] 观点: ...
[00:15-00:25] 例子: ...
[00:25-00:30] CTA: ...
YouTube 长视频
时长: 5-20 分钟
结构:
1. 开头 Hook + 预告（30 秒）
2. 片头（5 秒）
3. 正文分段（每段 2-4 分钟）
4. 过渡句衔接
5. 总结 + CTA（30 秒）
格式:
## 第 1 段: [标题]
[时间戳] 画面描述
旁白: "..."
字幕: "..."
教学 / 教程视频
时长: 3-15 分钟
结构:
1. 学习目标（这个视频你将学到...）
2. 前置知识
3. 分步教学（Step by step）
4. 实操演示描述
5. 总结 + 练习建议
格式:
## Step 1: [操作名称]
画面: [屏幕录制 / 实拍描述]
旁白: "首先我们需要..."
提示: [重要提示框]
产品演示视频
时长: 1-5 分钟
结构:
1. 痛点引入（你是否遇到过...）
2. 解决方案引出
3. 功能演示（3-5 个核心功能）
4. 用户证言 / 数据
5. CTA（试用/购买）
执行方式
直接使用 LLM 能力生成脚本，无需外部工具。
信息收集
如果用户没有提供足够信息，主动询问：
- 视频类型和时长
- 目标观众是谁
- 核心要表达什么
- 视频风格（专业/轻松/幽默）
- 是否需要分镜描述
输出规范
- 标注每段的时间戳
- 区分旁白/字幕/画面描述
- 短视频标注预估时长
- 长视频提供章节时间戳
- 附带拍摄/剪辑建议
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.
- 9d ago First seen · 110 lines · 34 tokens per session scan A a88fdfb7cf7c
video-script-writer is a skill published in the GitHub repository malue-ai/dazee-small (36 stars, last pushed 5mo ago), licensed MIT. It adds 34 tokens to every session and 752 once invoked, about $0.0002 per session on Opus 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…