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.
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 alchaincyf/huashu-skills --skill huashu-douyin-scriptgit clone --depth 1 https://github.com/alchaincyf/huashu-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/alchaincyf/huashu-skills/huashu-douyin-script)<a href="https://agentmods.dev/skills/alchaincyf/huashu-skills/huashu-douyin-script"><img src="https://agentmods.dev/badge/skills/alchaincyf/huashu-skills/huashu-douyin-script/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/alchaincyf/huashu-skills/huashu-douyin-script"><img src="https://agentmods.dev/badge/skills/alchaincyf/huashu-skills/huashu-douyin-script.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket warn
- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high YARA Match · line 56 YARA rule matched a known malware signature (reverse shell, backdoor, ransomware, C2 framework, or info stealer).Fix: Remove the malware payload or compromised file entirely. Investigate how it entered the skill and audit all other artifacts for additional indicators of compromise.
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 | $0.00125 | $0.04204 |
| Opus 5.5 | $0.00050 | $0.01682 |
| Sonnet 5.5 | $0.00025 | $0.00841 |
| Haiku 4.5 | $0.00013 | $0.00420 |
Grade A, and why
huashu-douyin-script 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.
How it starts
The opening of the file, as written. The whole thing — 374 lines — stays where its author put it; the contents beside it link to each section on GitHub.
抖音爆款脚本创作
从竞品视频拆解到脚本生成的完整工作流。将「凭感觉模仿爆款」变成「AI系统拆解+结构化复制」。
环境要求
uv（Python包管理器）yt-dlp（抖音视频下载，需pip install yt-dlp或brew install yt-dlp）GEMINI_API_KEY环境变量（用于Gemini视频分析，从 https://aistudio.google.com/apikey 获取）GEMINI_BASE_URL环境变量（可选，自定义API端点如代理/中转，不设置则用官方端点）- Chrome浏览器已登录抖音（用于提取下载Cookie）
路径约定：下文中 SKILL_DIR 指本SKILL.md所在目录的绝对路径。运行脚本前，先用 dirname 或 Glob 工具确定SKILL.md的实际位置，替换 SKILL_DIR。
6步工作流
Step 1: 收集输入
向用户收集以下信息：
必填：
- 抖音视频链接（1-5个对标/竞品视频）
- 产品信息（名称、核心卖点、目标人群、价格）
- 脚本类型：种草视频 or 千川投放素材
选填：
- 产品图片（用于脚本中的视觉参考）
- 目标时长（种草默认30秒，千川默认15秒）
- 品牌调性要求
- 投放目标（直播间引流/商品详情页/关注转化）
如果用户只提供了部分信息，主动询问缺失项。
Step 2: 下载视频
运行下载脚本：
uv run SKILL_DIR/scripts/download_douyin.py \
--urls "URL1" "URL2" \
--output-dir _temp/douyin-downloads
参数说明：
--urls：支持短链、页面链接、分享文本（自动提取URL）--output-dir：默认当前工作目录下_temp/douyin-downloads/--cookies-browser：默认chrome，可选edge/firefox
下载失败时：
- 提示用户确认Chrome已登录抖音
- 建议手动下载视频放入
_temp/douyin-downloads/ - 如果有douyin-mcp-server可用，尝试通过MCP下载
Step 3: Gemini视频分析（可并行）
对每个下载成功的视频，调用 Gemini 视频分析：
uv run SKILL_DIR/scripts/analyze_video.py \
--video "_temp/douyin-downloads/douyin-1-xxx.mp4" \
--prompt "PROMPT_BELOW" \
--model flash \
--resolution medium \
--output "_temp/douyin-downloads/analysis-1.md"
使用flash模型 + medium分辨率（短视频足够，节省成本）。
多个视频可并行分析（用 run_in_background=true）。
爆款分析Prompt（传入 --prompt 参数）：
作为资深抖音电商视频分析师，请对这个视频进行7维度深度拆解。
特别注意：前3秒是最关键的部分，需要逐帧级别的详细拆解。
## 1. 钩子分析（前3秒）⭐ 最关键
前3秒 = 文案钩子 + 视觉钩子，两条线都要详细分析。
### 1a. 文案钩子
- 钩子类型（反常识/痛点/数据/场景/悬念/利益）
- 钩子文案完整转录
- 文案与产品的关联度（强关联/弱关联）
### 1b. 视觉钩子（逐帧描述）
- 第0秒画面：暂停在最开始，描述这一帧的构图、色调、主体
- 视觉钩子类型（视觉奇观/产品堆叠/画面突变/动作冲击/文字弹出/第一人称POV）
- 具体画面描述：景别、色调、运镜方式、特效、人物表情和动作
- 视觉信息密度：画面中同时出现了多少信息元素
### 1c. 文案×视觉配合
- 文案和画面是否同步强化同一个信息
- 声音设计：前3秒有无音效/BGM变化/人声语气变化
- 综合钩子强度评分（1-10）及理由
## 2. 分镜结构
用表格拆解每个镜头：
| 时间 | 景别 | 画面内容 | 旁白/字幕 | 转场方式 |
## 3. 节奏设计
- 快切片段时间点
- 节奏变化模式（快-慢-快/渐进加速/脉冲式）
- BGM与画面的配合度
## 4. 视觉元素
- 色调和滤镜风格
- 字幕样式和出现时机
- 产品展示方式
- 构图特点
## 5. 转化设计
- CTA类型和出现时机
- 价格锚定策略
- 紧迫感营造手段
- 转化路径（视频→?→?）
## 6. 合规检查
- 是否存在绝对化用语
- 功效表述是否合规
- 有无潜在审核风险
## 7. 可复制要素
- 可直接复制的：钩子句式、分镜结构、视觉风格、CTA话术
- 不可复制的：独特场景、特定达人、品牌势能
请用中文输出，尽量详细。
What ships with it
6 files 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 · 374 lines · 125 tokens per session scan A b6ca5501cecd
huashu-douyin-script is a skill published in the GitHub repository alchaincyf/huashu-skills (2,025 stars, last pushed yesterday), licensed MIT. It adds 125 tokens to every session and 4,204 once invoked, about $0.0005 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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