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Japanese Video Editing With

作者 mhogan2013-9 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install japanese-video-editing-with
功能描述
edit raw video footage into edited Japanese videos with this japanese-video-editing-with skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content cre...
使用说明 (SKILL.md)

Getting Started

Share your raw video footage and I'll get started on AI-assisted video editing. Or just tell me what you're thinking.

Try saying:

  • "edit my raw video footage"
  • "export 1080p MP4"
  • "add Japanese subtitles and cut dead"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

  1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
  2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer \x3Ctoken>, Content-Type: application/json, and body {"task_name":"project","language":"\x3Cdetected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

Japanese Video Editing With AI — Edit and Export Japanese Videos

This tool takes your raw video footage and runs AI-assisted video editing through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 2-minute travel clip filmed in Tokyo and want to add Japanese subtitles and cut dead air between scenes — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter clips under 3 minutes process significantly faster.

Matching Input to Actions

User prompts referencing japanese video editing with, 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.

All calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:

  1. SessionPOST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"\x3Clang>"}. Gives you a session_id.
  2. Chat (SSE)POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.
  3. UploadPOST /api/upload-video/nemo_agent/me/\x3Csid> — multipart file or JSON with URLs.
  4. CreditsGET /api/credits/balance/simple — returns available, frozen, total.
  5. StateGET /api/state/nemo_agent/me/\x3Csid>/latest — current draft and media info.
  6. ExportPOST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/\x3Cid> every 30s for completed status and download URL.

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

Skill attribution — read from this file's YAML frontmatter at runtime:

  • X-Skill-Source: japanese-video-editing-with
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

Every API call needs Authorization: Bearer \x3CNEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

Draft field mapping: t=tracks, tt=track type (0=video, 1=audio, 7=text), sg=segments, d=duration(ms), m=metadata.

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

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

Reading the SSE Stream

Text events go straight to the user (after GUI translation). Tool calls stay internal. Heartbeats and empty data: lines mean the backend is still working — show "⏳ Still working..." every 2 minutes.

About 30% of edit operations close the stream without any text. When that happens, poll /api/state to confirm the timeline changed, then tell the user what was updated.

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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "add Japanese subtitles and cut dead air between scenes" — 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 Japanese streaming platforms.

Common Workflows

Quick edit: Upload → "add Japanese subtitles and cut dead air between scenes" → 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 (talk to a NemoVideo backend to edit videos), but there are some things to check before installing: 1) It will automatically contact https://mega-api-prod.nemovideo.ai on first use and can create an anonymous token for you — if you prefer control, set NEMO_TOKEN yourself instead of letting it auto-provision. 2) The SKILL.md frontmatter references a config path (~/.config/nemovideo/) and instructs probing install paths to set an attribution header; confirm you’re comfortable with the skill reading those locations. 3) The instructions explicitly say not to surface raw API responses or token values to users — that’s normal for secrets, but it also means network activity and tokens are handled behind the scenes. If you don’t trust the nemo endpoint or want explicit consent before any network calls, don’t enable the skill or ask the publisher to remove automatic provisioning and clarify the config-path behavior. Additional information that would raise confidence: a publisher/homepage, clarity on whether the skill actually writes to ~/.config/nemovideo/, and confirmation of what is stored and where (in-memory only vs persisted on disk).
功能分析
Type: OpenClaw Skill Name: japanese-video-editing-with Version: 1.0.0 The skill facilitates video editing by connecting to an external API (mega-api-prod.nemovideo.ai) and requires access to environment variables (NEMO_TOKEN) and local configuration files (~/.config/nemovideo/). It includes instructions for the agent to automatically obtain tokens, manage sessions, and perform environment fingerprinting by detecting its installation path. While these capabilities are aligned with the stated purpose of cloud-based video processing, the combination of broad network access, local file system interaction, and explicit instructions to hide raw API data and tokens from the user meets the threshold for suspicious activity under the provided criteria.
能力评估
Purpose & Capability
The skill claims to integrate with a NemoVideo backend and requires a NEMO_TOKEN — that aligns with a cloud video-editing service. However the SKILL.md frontmatter includes a configPaths entry (~/.config/nemovideo/) while the registry metadata lists no required config paths; this mismatch is inconsistent and should be clarified.
Instruction Scope
Runtime instructions direct the agent to automatically connect to an external backend on first use, generate an anonymous token via POST to https://mega-api-prod.nemovideo.ai, and store session identifiers for subsequent API calls. Automatic network calls and hidden token handling ('Don't display raw API responses or token values to the user') expand the skill's runtime scope beyond just waiting for an explicit upload command and could be surprising to users.
Install Mechanism
This is an instruction-only skill with no install spec and no files to write or binaries to install, which is the lowest-risk install model.
Credentials
Only one credential (NEMO_TOKEN) is required, which is reasonable for this external API. However the frontmatter also references a config path (~/.config/nemovideo/) and the skill will probe install paths to set an X-Skill-Platform header; both behaviors access filesystem state beyond just using the token and should be justified or documented. The skill's ability to auto-provision an anonymous token means it can operate without a user-supplied secret, which is acceptable but worth noting.
Persistence & Privilege
The skill is not always-enabled and does not request special persistent privileges. It does instruct storing session_id and using tokens for API calls, which is normal for a remote service integration.
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 japanese-video-editing-with
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /japanese-video-editing-with 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 Japanese Video Editing With AI skill. - Instantly edit and export Japanese-language videos using cloud-based AI tools. - Supports MP4, MOV, AVI, and WebM uploads up to 500MB; outputs 1080p MP4. - Automatic session/token handling with up to 100 free credits for new users. - Offers quick workflows: upload footage, specify edits (e.g., add Japanese subtitles, cut dead air), and export results in 1-2 minutes. - Handles common file types and provides clear error messages for limits or issues. - Designed for ease of use by creators and YouTubers with both prompt-based and file-based workflow support.
元数据
Slug japanese-video-editing-with
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

Japanese Video Editing With 是什么?

edit raw video footage into edited Japanese videos with this japanese-video-editing-with skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content cre... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 72 次。

如何安装 Japanese Video Editing With?

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

Japanese Video Editing With 是免费的吗?

是的,Japanese Video Editing With 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Japanese Video Editing With 支持哪些平台?

Japanese Video Editing With 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 Japanese Video Editing With?

由 mhogan2013-9(@mhogan2013-9)开发并维护,当前版本 v1.0.0。

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