Install the "prompt-translator" agent skill from https://github.com/cclank/lanshu-awesome-ai-video-kit/tree/main/skills/prompt-translator into .claude/skills/prompt-translator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "prompt-translator", then confirm the skill loads.
Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
skills CLI
$ npx skills add cclank/lanshu-awesome-ai-video-kit --skill prompt-translator -a codex
Project install goes to .agents/skills/; add -g for ~/.codex/skills/.
Install the "prompt-translator" agent skill from https://github.com/cclank/lanshu-awesome-ai-video-kit/tree/main/skills/prompt-translator into .agents/skills/prompt-translator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "prompt-translator", then confirm the skill loads.
Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
skills CLI
$ npx skills add cclank/lanshu-awesome-ai-video-kit --skill prompt-translator -a cursor
Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.
Install the "prompt-translator" agent skill from https://github.com/cclank/lanshu-awesome-ai-video-kit/tree/main/skills/prompt-translator into .cursor/skills/prompt-translator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "prompt-translator", then confirm the skill loads.
Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
skills CLI
$ npx skills add cclank/lanshu-awesome-ai-video-kit --skill prompt-translator -a gemini-cli
Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.
Install the "prompt-translator" agent skill from https://github.com/cclank/lanshu-awesome-ai-video-kit/tree/main/skills/prompt-translator into .gemini/skills/prompt-translator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "prompt-translator", then confirm the skill loads.
Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
skills CLI
$ npx skills add cclank/lanshu-awesome-ai-video-kit --skill prompt-translator -a github-copilot
Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.
Install the "prompt-translator" agent skill from https://github.com/cclank/lanshu-awesome-ai-video-kit/tree/main/skills/prompt-translator into .github/skills/prompt-translator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "prompt-translator", then confirm the skill loads.
GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
skills CLI
$ npx skills add cclank/lanshu-awesome-ai-video-kit --skill prompt-translator -a opencode
OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
Install the "prompt-translator" agent skill from https://github.com/cclank/lanshu-awesome-ai-video-kit/tree/main/skills/prompt-translator into .opencode/skills/prompt-translator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "prompt-translator", then confirm the skill loads.
OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
Skill name
prompt-translator
GitHub stars
415
Token cost
~2k tokens
SKILL.md length
465 words
Files
1
Skills in repo
7
Repo updated
First seen
Licence
MIT
At a glance
把一条 AI 视频提示词从源模型(如 Sora 2)的写法风格转换为目标模型(如 Kling 3.0 / Wan 2.7 / Veo 3.1 等)的最佳实践写法。基于 110 条 10 场景 × 11 模型对照基准数据(prompts/data/cross-model-matrix.json),不是凭直觉重写,而是查表式 in-context learning。10 场景:产品 / 双人对话…
Works in 3 steps: [ ] 目标 prompt 有没有上表对应的标签/结构? → [ ] 数据库 cross-model-matrix.json 中该模型该场景的… → [ ] 如果不一致,重写,不要凑合。
Tasks that involve AI video generation
SKILL.md covers 何时不用此 skill, 核心数据资产, 工作流程 and 实战示例, plus 3 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Media & Creative, covering AI video generation and Translation. It works with Google Veo. The repository describes itself as: 做企业 AI 视频项目逼出来的工具包 · 411 prompt · 15 模型 · 7 Claude Skill · 14 篇方法论. The licence is MIT.
When your agent uses it
Tasks that involve AI video generation
Tasks that involve Translation
Example prompts
“Sora 已 EOL 帮我把这条提示词改成 Veo”
“我有 Kling 提示词想跑 Wan”
“跨模型 A/B 测试”
“/prompt-translator”
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit f4c1bbd. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Prompt Translator loads about 2k tokens when it runs. Until then it costs about 90 tokens; SKILL.md has 465 words of instructions outside code blocks.
Always· name and description, kept in context so the agent knows when to use it
~90
When it runs· the whole SKILL.md, loaded when a task matches
~2k
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
Style: 1970s romantic drama, 35mm film with warm halation, slight handheld micro-shake.
A park bench at golden hour in late autumn. Two men in their early 30s.
Cinematography: Medium-wide, slow dolly-in. 40mm lens, shallow focus.
Actions:
- A sits down hesitantly
- A (low, hesitant): "It's been a long time."
- B turns, eyes widening
- B (warm): "Too long. I almost didn't recognize you."
- Both share a quiet laugh
Background Sound: Soft piano, ambient park, no music swell.
## 转换结果
**源模型**: Sora 2 · **目标模型**: Kling 3.0
**参考场景**: scene-2-reunion(情感双人对话)
\`\`\`
Scene: A park bench at golden hour in late autumn, amber sunlight filtering through bare branches, fall leaves drifting through the frame.
Characters: Character A (early 30s, hesitant) and Character B (early 30s, expressive).
Action: A walks up and sits down beside B with visible hesitation. A says: "It's been a long time." B turns slowly, eyes widening with recognition, replies warmly: "Too long. I almost didn't recognize you." They share a quiet laugh that breaks the tension.
Camera: Slow push-in on A as he speaks, over-the-shoulder cut to B's reaction, ending on a held wide two-shot.
Audio & Style: Soft solo piano underscore building gently, ambient park sounds (distant kids playing, leaves rustling), warm cinematic teal-and-amber grade, 1970s romantic drama with 35mm halation aesthetic, naturalistic dialogue delivery.
\`\`\`
## 转换映射
| Sora 2 | Kling 3.0 | 注释 |
|---|---|---|
| Style: ... | (合并到 Audio & Style:) | Kling 5 层把 Style 嵌在最后一层 |
| Cinematography: 段 | Camera: | 字段重命名,Kling 更简洁 |
| Actions: beats + dialogue 嵌入 | Action: 自然语言 + 嵌入对白 | Kling 5 层 Action 段直接含对白,不像 Sora 用 beats 列表 |
| Background Sound: | (合并到 Audio & Style:) | Kling 把音频与视觉风格放一段 |
| (无 Characters: 段) | Characters: 显式列角色 | Kling 5 层强制要求 Characters: 段 |
## 注意事项
- ✅ Kling 5 层结构能很好承接 Sora 的所有内容
- 💡 推荐参数:16:9 / 10s / 1080p
- 🌐 Kling 中文理解优于 Sora,如果场景偏中式可把对白和场景描述改成中文(Kling 中文是业界并列第一)
- 🔄 如果想要更强的音画对白同步,再转 Veo 3.1(原生音频最强)
Prompt Translator next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
Prompt Translator compared with similar skills
Skill
Stars
Used in
Tokens
Auto-check
Licence
Repo updated
Prompt Translator this skillcclank/lanshu-awesome-ai-video-kit
This skill should be used when the user asks for Spanish Seedance 2.0 prompt wording, Spanish cinematic vocabulary, or translation of camera, lighting, action, VFX, audio, and production terms into…
This skill should be used when the user asks for Japanese Seedance 2.0 prompt wording, Japanese cinematic vocabulary, or translation of camera, lighting, action, VFX, audio, and production terms…
This skill should be used when the user asks for Korean Seedance 2.0 prompt wording, Korean cinematic vocabulary, or translation of camera, lighting, action, VFX, audio, and production terms into…
This skill should be used when the user asks for Russian Seedance 2.0 prompt wording, Russian cinematic vocabulary, or translation of camera, lighting, action, VFX, audio, and production terms into…
Generates an image or an image-to-video clip through a configured provider API or a signed-in Codex or Grok CLI, and reports the route, file, hash and cost estimate.
把一条 AI 视频提示词从源模型(如 Sora 2)的写法风格转换为目标模型(如 Kling 3.0 / Wan 2.7 / Veo 3.1 等)的最佳实践写法。基于 110 条 10 场景 × 11 模型对照基准数据(prompts/data/cross-model-matrix.json),不是凭直觉重写,而是查表式 in-context learning。10 场景:产品 / 双人对话…. Prompt Translator is an agent skill from cclank/lanshu-awesome-ai-video-kit.
When should I use Prompt Translator?
Prompt Translator fits situations like: tasks that involve AI video generation; tasks that involve Translation.
How do I install Prompt Translator in Claude Code?
Run `npx skills add cclank/lanshu-awesome-ai-video-kit --skill prompt-translator -a claude-code`. Or copy the skill folder (skills/prompt-translator in cclank/lanshu-awesome-ai-video-kit) into .claude/skills/prompt-translator in your project. Claude Code loads it when a task matches its description.
How do I install Prompt Translator in Codex?
Run `npx skills add cclank/lanshu-awesome-ai-video-kit --skill prompt-translator -a codex`. Or copy the skill folder (skills/prompt-translator in cclank/lanshu-awesome-ai-video-kit) into .agents/skills/prompt-translator in your project. Codex loads it when a task matches its description.
Can I use Prompt Translator in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add cclank/lanshu-awesome-ai-video-kit --skill prompt-translator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/prompt-translator, .gemini/skills/prompt-translator, .github/skills/prompt-translator and .opencode/skills/prompt-translator in your project.
What does Prompt Translator need to run?
SKILL.md names no scripts, command-line tools or credentials: Prompt Translator is instructions for the agent only.
Does Prompt Translator access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Prompt Translator safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Prompt Translator use?
Prompt Translator is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Prompt Translator use?
About 2k tokens (SKILL.md is roughly 7.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Prompt Translator?
Skills that share tags, products or a category with Prompt Translator: Seedance Vocab Es (Emily2040/seedance-2.0, 7.6k stars), Seedance Vocab Ja (Emily2040/seedance-2.0, 7.6k stars), Seedance Vocab Ko (Emily2040/seedance-2.0, 7.6k stars) and Seedance Vocab Ru (Emily2040/seedance-2.0, 7.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Prompt Translator?
cclank (a GitHub user) maintains it in cclank/lanshu-awesome-ai-video-kit, which has 415 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on October 7, 2026.
