huashu-video-outline

huashu-video-outline is a skill for Claude Code, Codex from alchaincyf/huashu-skills. It costs 56 tokens per session (686 once invoked), scanned A, original, MIT.

A Chinese video-planning tool that creates two or three outline options with titles, thumbnail suggestions, and a proposed structure.

In plain words
What is it for?
Use it to plan video topics, titles, thumbnails, and script structure.
Why use it?
It helps turn a video idea into a clear plan before writing the full script or recording.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to plan video topics, titles, thumbnails, and script structure.

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Install with agentmods
npx agentmods add skills/alchaincyf/huashu-skills/huashu-video-outline
About the project

huashu-skills is a catalogue of Agent Skills, which are reusable instruction packages that extend coding agents such as Claude Code, Codex, and Kimi Code for particular tasks. It organizes skills for design, research, document conversion, content creation, and other workflows, and includes machine-readable metadata and update checking. The catalogue entries are the skills and related tools that agents install and use.

alchaincyf/huashu-skills · 2,025 stars · on GitHub

Install

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.

Any agent
npx skills add alchaincyf/huashu-skills --skill huashu-video-outline
Clone the repo
git clone --depth 1 https://github.com/alchaincyf/huashu-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for huashu-video-outline

README.md
[![agentmods](https://agentmods.dev/badge/skills/alchaincyf/huashu-skills/huashu-video-outline/github.svg)](https://agentmods.dev/skills/alchaincyf/huashu-skills/huashu-video-outline)
Your own site
<a href="https://agentmods.dev/skills/alchaincyf/huashu-skills/huashu-video-outline"><img src="https://agentmods.dev/badge/skills/alchaincyf/huashu-skills/huashu-video-outline/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.

agentmods 80×15 button for huashu-video-outline

Your own site · 80×15
<a href="https://agentmods.dev/skills/alchaincyf/huashu-skills/huashu-video-outline"><img src="https://agentmods.dev/badge/skills/alchaincyf/huashu-skills/huashu-video-outline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 56 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 686 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 15 Sept 2026
  • Snyk pass 15 Sept 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00056 $0.00686
Opus 5.5 $0.00022 $0.00274
Sonnet 5.5 $0.00011 $0.00137
Haiku 4.5 $0.00006 $0.00069

Measured 1mo ago against content hash 434439278a44, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

huashu-video-outline 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.

huashu-video-outline/SKILL.md · 74 lines

What it actually says

视频大纲生成

快速生成2-3个视频脚本大纲方案,包含标题、封面建议、结构设计。

何时使用

  • 保存视频brief后
  • 用户说"提供大纲"、"给几个方案"
  • 视频创作流程的Step 3(大纲讨论)

核心功能

  1. 提供2-3个大纲方案:每个方案不同角度
  2. 每个方案包含:标题、封面建议、核心角度、大纲结构、时长预估
  3. 应用封标策略:5种强对比公式、封面设计策略

大纲方案模板

## 方案1:[吸引人的标题]
**封面建议**:结果展示/人脸(根据粉丝量)
**核心角度**:xxx
**时长预估**:⏱️ 5-8分钟

### 大纲结构
1. 开头(30秒-1分钟):确认标题承诺 + 建立悬念
2. 核心模块1(2分钟):xxx
3. 核心模块2(2分钟):xxx
4. 意外惊喜(1分钟):超出预期的内容
5. 结尾(1-2分钟):兑现承诺 + Call to Action

### 需要演示的内容
- 演示1:xxx
- 演示2:xxx

### 优势劣势
✅ 优势:xxx
⚠️ 劣势:xxx

标题策略(5种对比)

  1. 数量对比:"1个功能 vs 10个工具"
  2. 价格对比:"免费 vs 付费,差距有多大?"
  3. 结果对比:"0粉到30万粉,我做对了什么"
  4. 强弱对比:"新手 vs Cursor,谁能赢?"
  5. 时间对比:"3分钟 vs 3小时"

封面策略

  • < 10万粉:结果展示封面优先
  • > 10万粉:可测试人脸封面
  • 教程类:Before/After对比
  • 评测类:产品特写+数据

注意事项

  • 应用内容承接策略(开头确认→中段惊喜→结尾兑现)
  • 时长预估要合理
  • 等待用户选择,不假设

最后更新: 2025-11-07


花叔出品 | AI Native Coder · 独立开发者 公众号「花叔」| 30万+粉丝 | AI工具与效率提升 代表作:小猫补光灯(AppStore付费榜Top1)·《一本书玩转DeepSeek》

Changes

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.

  1. 1mo ago First seen · 74 lines · 56 tokens per session scan A 434439278a44

Subscribe to this mod's changes

huashu-video-outline is a skill published in the GitHub repository alchaincyf/huashu-skills (2,025 stars, last pushed yesterday), licensed MIT. It adds 56 tokens to every session and 686 once invoked, about $0.0002 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 2026-08-30.

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