aliang-shortvideo

aliang-shortvideo is a skill for Claude Code, Codex from aliang2052/aliang-skills. It costs 242 tokens per session (2,571 once invoked), scanned A, original, MIT.

A step-by-step production workflow for turning a short idea into a Chinese short video: story outline, episode script, shot list, images, and a final video.

In plain words
What is it for?
Use it to create short dramas in several genres, write dialogue and storyboards, generate keyframe images with Alibaba's Bailian command-line tool, and prepare image-to-video commands.
Why use it?
It breaks a large creative task into reviewable stages, pausing for approval after each stage. Video generation is not run automatically because it may cost money.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: names the AskUserQuestion tool.

Good fit Use it to create short dramas in several genres, write dialogue and storyboards, generate keyframe images with Alibaba's Bailian command-line tool, and prepare image-to-video commands.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/aliang2052/aliang-skills/aliang-shortvideo
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 aliang2052/aliang-skills --skill aliang-shortvideo
Clone the repo
git clone --depth 1 https://github.com/aliang2052/aliang-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 aliang-shortvideo

README.md
[![agentmods](https://agentmods.dev/badge/skills/aliang2052/aliang-skills/aliang-shortvideo/github.svg)](https://agentmods.dev/skills/aliang2052/aliang-skills/aliang-shortvideo)
Your own site
<a href="https://agentmods.dev/skills/aliang2052/aliang-skills/aliang-shortvideo"><img src="https://agentmods.dev/badge/skills/aliang2052/aliang-skills/aliang-shortvideo/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 aliang-shortvideo

Your own site · 80×15
<a href="https://agentmods.dev/skills/aliang2052/aliang-skills/aliang-shortvideo"><img src="https://agentmods.dev/badge/skills/aliang2052/aliang-skills/aliang-shortvideo.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 242 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,571 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.
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 $0.00242 $0.02571
Opus 5 $0.00121 $0.01286
Sonnet 5 $0.00048 $0.00514
Haiku 4.5 $0.00024 $0.00257

Measured 12d ago against content hash f51c63f5b9f5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

aliang-shortvideo 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 12d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/gen_images.py, scripts/pick_beats.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/aliang-shortvideo/SKILL.md · 108 lines

How it starts

The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.

短剧全流程制作流水线

把一句话灵感做成可播短剧,五阶段、每步暂停确认

① 剧情大纲 → ② 分集剧本(台词) → ③ 分镜表(枢纽) → ④ 批量出图 → ⑤ 图生视频(成片)

⚠️ 视频生成费钱。①~④ 可放心跑;⑤ 图生视频默认不自动实跑——开发/测试/演示时只产出每段的 bl video 命令交给用户,或等用户显式确认要为某段付费,再逐段生成。功能要做全,钱不替用户烧。

前置

  • bl(百炼 CLI)可用并已登录(bl auth status 可查)。出图阶段需要它。
  • 开工先确认 4 件事,其余用默认:① 一句话灵感(必问);② 题材(用 AskUserQuestion 给 3-4 个高频项让用户选,见 references/genres.md);③ 总时长(用 AskUserQuestion 给 15s / 30s / 60s + 自定义;用户已在灵感里说了时长就别再问);④ 画风(用 AskUserQuestion 从 references/styles.md 的 22 个预设里让用户挑,分写实/动漫/3D-CG/插画/风格化 5 类;按题材把最搭的放第一标「(推荐)」。问画风时务必明确邀请上传参考图:在选项里加一项「📎 我发一张参考图(照着这张的画风做)」,并提示用户可直接把图片拖/粘贴进对话、或给本地路径/URL。用户发了图就走参考图模式,见下条)。画风是画面质量的头号变量,必须开工就定,别拖到出图。比例默认竖版 9:16、单镜默认 5s,用户没要求就别追问。
  • 时长换算:图片张数 ≈ 总时长 ÷ 5(每 5s 一镜一张)。15s≈3 张、30s≈6 张、60s≈12 张。总时长定了,镜数就定了。
  • 可选·参考图:用户甩了参考图(海报/截图/角色图)时,别只靠肉眼翻译——① 用 bl vision 把它读成一段精准的 style 串;② 把图路径填进 storyboard.jsonstyle_ref,出图脚本会用 bl image edit 直接迁移这张图的画风,还原度更高。两者可并用。

工作流

阶段 ① 剧情大纲

  1. 确认题材后,读 references/genres.md 取该题材的爽点库 + 结构模板 + 红线
  2. 抽爽点:跑 python3 scripts/pick_beats.py --genre <题材>(真随机抽 8-12 个,避免套路雷同)。
  3. 按该题材结构写约 500 字纯叙事大纲,融入抽到的爽点,遵守反套路 + 内容健康红线。
  4. 输出大纲 + 列出本次用的爽点 + 逆袭/反转路径标注。
  5. 暂停:请用户确认大纲走向,改完再进下一阶段。

阶段 ② 分集剧本

把大纲扩成可拍剧本:

  • 按节奏切场(每场一个地点+冲突单元),标注 场景 / 人物 / 动作 / 台词
  • 台词口语化、短、有冲突感;旁白克制。
  • 黄金 3 秒原则:第一场就抛冲突/悬念。
  • 短剧分集可选:若用户要多集,每集结尾留扣。
  • 暂停:用户确认剧本,再进分镜。

阶段 ③ 分镜表(枢纽)

references/storyboard.md,产出两份同源数据

  1. 给人看的分镜表格(镜号/时长/景别/运镜/画面/角色动作/台词/情绪)。
  2. 给脚本用的 storyboard.json(存到项目目录),含全片统一 style、固定 characters[].desc、每镜 image_prompt

关键:

  • 镜数由总时长定:镜数 ≈ 总时长 ÷ 5(单镜默认 5s)。先按这个铺满镜数,再按剧情节奏微调。
  • 单镜时长用户可逐镜调:分镜表每镜都有「时长」列,用户可指定某镜 5s/10s/15s。给某镜 10s/15s 时,按 5s 为单位拆成多个子镜(视频阶段每段 5s),图片阶段每个子镜出 1 张——所以加长某镜会增加该镜的图片数。拆完把总时长/总张数报给用户对一下。
  • image_prompt 只写画面,不写台词/镜号。
  • 落实画风:把开工选定的画风预设(references/styles.md 里的 style 串)写进 storyboard.jsonstyle;有参考图就填 style_ref。此处只做应用/微调,不重新问(开工已定)。
  • 先定全片 style 串和主角 desc(一致性命脉,见 storyboard.md 第六节)。
  • 暂停:用户确认分镜 + 各镜时长 + 画风,再出图。

Read the full file on GitHub · 108 lines

Files

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.

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. 12d ago First seen · 108 lines · 242 tokens per session scan A f51c63f5b9f5

Subscribe to this mod's changes

aliang-shortvideo is a skill published in the GitHub repository aliang2052/aliang-skills (26 stars, last pushed 3mo ago), licensed MIT. It adds 242 tokens to every session and 2,571 once invoked, about $0.0012 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 2026-08-30.

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