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tk8544-b

Language Editor

作者 tk8544-b · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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当前安装
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在 OpenClaw 中安装
/install language-editor
功能描述
Get translated dubbed videos ready to post, without touching a single slider. Upload your video with audio (MP4, MOV, AVI, WebM, up to 500MB), say something...
使用说明 (SKILL.md)

Getting Started

Share your video with audio and I'll get started on AI language editing. Or just tell me what you're thinking.

Try saying:

  • "convert my video with audio"
  • "export 1080p MP4"
  • "translate the spoken audio into French"

Automatic Setup

On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".

Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.

Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: \x3Cuuid>. The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).

Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.

Confirm to the user you're connected and ready. Don't print tokens or raw JSON.

Language Editor — Translate and Dub Videos Instantly

Drop your video with audio in the chat and tell me what you need. I'll handle the AI language editing on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 3-minute tutorial video in English, ask for translate the spoken audio into French and sync the new voiceover to the video, and about 1-2 minutes later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter clips under 5 minutes produce the most accurate lip-sync results.

Matching Input to Actions

User prompts referencing language editor, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

User says... Action Skip SSE?
"export" / "导出" / "download" / "send me the video" → §3.5 Export
"credits" / "积分" / "balance" / "余额" → §3.3 Credits
"status" / "状态" / "show tracks" → §3.4 State
"upload" / "上传" / user sends file → §3.2 Upload
Everything else (generate, edit, add BGM…) → §3.1 SSE

Cloud Render Pipeline Details

Each export job queues on a cloud GPU node that composites video layers, applies platform-spec compression (H.264, up to 1080x1920), and returns a download URL within 30-90 seconds. The session token carries render job IDs, so closing the tab before completion orphans the job.

Base URL: https://mega-api-prod.nemovideo.ai

Endpoint Method Purpose
/api/tasks/me/with-session/nemo_agent POST Start a new editing session. Body: {"task_name":"project","language":"\x3Clang>"}. Returns session_id.
/run_sse POST Send a user message. Body includes app_name, session_id, new_message. Stream response with Accept: text/event-stream. Timeout: 15 min.
/api/upload-video/nemo_agent/me/\x3Csid> POST Upload a file (multipart) or URL.
/api/credits/balance/simple GET Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/\x3Csid>/latest GET Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda POST Start export. Body: {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll status every 30s.

Accepted file types: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is language-editor, X-Skill-Version comes from the version field, and X-Skill-Platform is detected from the install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, otherwise unknown).

Include Authorization: Bearer \x3CNEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

Error Codes

  • 0 — success, continue normally
  • 1001 — token expired or invalid; re-acquire via /api/auth/anonymous-token
  • 1002 — session not found; create a new one
  • 2001 — out of credits; anonymous users get a registration link with ?bind=\x3Cid>, registered users top up
  • 4001 — unsupported file type; show accepted formats
  • 4002 — file too large; suggest compressing or trimming
  • 400 — missing X-Client-Id; generate one and retry
  • 402 — free plan export blocked; not a credit issue, subscription tier
  • 429 — rate limited; wait 30s and retry once

SSE Event Handling

Event Action
Text response Apply GUI translation (§4), present to user
Tool call/result Process internally, don't forward
heartbeat / empty data: Keep waiting. Every 2 min: "⏳ Still working..."
Stream closes Process final response

~30% of editing operations return no text in the SSE stream. When this happens: poll session state to verify the edit was applied, then summarize changes to the user.

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend says You do
"click [button]" / "点击" Execute via API
"open [panel]" / "打开" Query session state
"drag/drop" / "拖拽" Send edit via SSE
"preview in timeline" Show track summary
"Export button" / "导出" Execute export workflow

Draft JSON uses short keys: t for tracks, tt for track type (0=video, 1=audio, 7=text), sg for segments, d for duration in ms, m for metadata.

Example timeline summary:

Timeline (3 tracks): 1. Video: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "translate the spoken audio into French and sync the new voiceover to the video" — concrete instructions get better results.

Max file size is 500MB. Stick to MP4, MOV, AVI, WebM for the smoothest experience.

Export as MP4 for widest compatibility across platforms and devices.

Common Workflows

Quick edit: Upload → "translate the spoken audio into French and sync the new voiceover to the video" → Download MP4. Takes 1-2 minutes for a 30-second clip.

Batch style: Upload multiple files in one session. Process them one by one with different instructions. Each gets its own render.

Iterative: Start with a rough cut, preview the result, then refine. The session keeps your timeline state so you can keep tweaking.

安全使用建议
This skill appears to do what it says: it will upload any video you provide to a third-party API (mega-api-prod.nemovideo.ai) and requires a NEMO_TOKEN (or will obtain a short-lived anonymous token). Before installing or using it, consider: 1) only upload non-sensitive videos (privacy risk — your media is sent to their servers); 2) confirm you trust the nemovideo.ai service and its data retention/privacy policies; 3) verify how/where the NEMO_TOKEN will be stored in your environment if you supply one (don’t reuse high-privilege tokens); 4) note the small metadata inconsistency (~/.config/nemovideo/ listed in SKILL.md frontmatter) — ask the author whether the skill will read/write that path; and 5) test with a short non-confidential clip first. If you want higher assurance, ask the publisher for their homepage/source and a privacy/security statement before use.
能力评估
Purpose & Capability
Name/description (translate & dub videos) match the runtime instructions: the SKILL.md describes uploading video files and calling nemovideo.ai endpoints. Requiring a NEMO_TOKEN (and providing an anonymous-token fallback) is consistent with this purpose.
Instruction Scope
Instructions focus on session creation, file upload, SSE streaming, and exports to the nemovideo.ai API — all expected. It also instructs constructing attribution headers (including detecting install path) and mentions a configPath (~/.config/nemovideo/) in the frontmatter; the skill does not explicitly say to read that path, so there is a small mismatch between metadata and runtime guidance.
Install Mechanism
No install spec and no code files — instruction-only. This is the lowest-risk install profile (nothing written to disk by the skill itself).
Credentials
Only one credential is requested (NEMO_TOKEN), which aligns with the described API usage. The skill also allows creating an anonymous token by POSTing a generated UUID. The frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata shows no required config paths; this discrepancy is worth noting but not necessarily malicious.
Persistence & Privilege
always is false and the skill does not request elevated/system-wide persistence. Agent autonomous invocation remains enabled (platform default) but that is not a red flag by itself.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install language-editor
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /language-editor 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
- Initial release of Language Editor for instant video translation and dubbing. - Upload videos (up to 500MB), specify target language, and receive dubbed 1080p MP4 output. - Automatic handling of session, credits, and cloud processing setup — no manual configuration required. - Supports export, credit checking, timeline state, and multiple file types. - Optimized for fast workflows for content creators and educators needing quick language adaptation.
元数据
Slug language-editor
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Language Editor 是什么?

Get translated dubbed videos ready to post, without touching a single slider. Upload your video with audio (MP4, MOV, AVI, WebM, up to 500MB), say something... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 79 次。

如何安装 Language Editor?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install language-editor」即可一键安装,无需额外配置。

Language Editor 是免费的吗?

是的,Language Editor 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Language Editor 支持哪些平台?

Language Editor 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Language Editor?

由 tk8544-b(@tk8544-b)开发并维护,当前版本 v1.0.0。

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