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Jianying Editor

作者 dsewell-583h0 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install jianying-editor
功能描述
Get edited video clips ready to post, without touching a single slider. Upload your raw video footage (MP4, MOV, AVI, MKV, up to 500MB), say something like "...
使用说明 (SKILL.md)

Getting Started

Send me your raw video footage and I'll handle the AI video editing. Or just describe what you're after.

Try saying:

  • "edit a 2-minute smartphone video clip into a 1080p MP4"
  • "cut the video, add background music, and apply auto captions"
  • "editing short-form videos for TikTok and Reels for TikTok creators"

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.

Jianying Editor — Edit and Export Video Clips

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

Say you have a 2-minute smartphone video clip and want to cut the video, add background music, and apply auto captions — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter clips under 60 seconds process significantly faster.

Matching Input to Actions

User prompts referencing jianying 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.

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: jianying-editor
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

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

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 Handling

Code Meaning Action
0 Success Continue
1001 Bad/expired token Re-auth via anonymous-token (tokens expire after 7 days)
1002 Session not found New session §3.0
2001 No credits Anonymous: show registration URL with ?bind=\x3Cid> (get \x3Cid> from create-session or state response when needed). Registered: "Top up credits in your account"
4001 Unsupported file Show supported formats
4002 File too large Suggest compress/trim
400 Missing X-Client-Id Generate Client-Id and retry (see §1)
402 Free plan export blocked Subscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429 Rate limit (1 token/client/7 days) Retry in 30s once

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "cut the video, add background music, and apply auto captions" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across social platforms.

Common Workflows

Quick edit: Upload → "cut the video, add background music, and apply auto captions" → 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 internally consistent for a cloud video-editing capability, but understand what that means before installing: uploaded videos and metadata will be sent to mega-api-prod.nemovideo.ai and processed there, and the skill needs a NEMO_TOKEN (or it will request a short-lived anonymous token). The skill may read your agent install path to populate an attribution header and may store session state (session_id) as part of normal operation. Verify you trust the nemovideo.ai service and avoid sending sensitive footage you wouldn't want uploaded to a third party. Also note the skill's source and homepage are unknown — if you need stronger assurance, ask the publisher for provenance or use a skill from a known provider.
功能分析
Type: OpenClaw Skill Name: jianying-editor Version: 1.0.0 The skill provides a functional interface for an AI video editing service hosted at nemovideo.ai. It handles session management, file uploads, and video rendering via a cloud pipeline as described in SKILL.md. While it performs automated network requests to fetch anonymous tokens and manage sessions, these actions are directly aligned with its stated purpose and include security-conscious instructions for the agent, such as suppressing the output of raw tokens or JSON. No indicators of data exfiltration, persistence, or malicious intent were found.
能力评估
Purpose & Capability
Name/description (video editing) aligns with required env var (NEMO_TOKEN), declared config path (~/.config/nemovideo/), and the documented API endpoints and upload/export workflow. Nothing requested appears unrelated to video editing.
Instruction Scope
The SKILL.md is instruction-only and directs the agent to authenticate (use NEMO_TOKEN or request an anonymous token), create a session, upload video files, use SSE for edits, and poll for export results — all appropriate for a cloud render pipeline. It also asks the agent to detect the agent install path (~/.clawhub/, ~/.cursor/skills/) to set an attribution header (X-Skill-Platform). Reading those install paths is a modest scope expansion beyond pure editing (it reveals filesystem layout) but is explained as attribution metadata rather than a functional necessity.
Install Mechanism
No install spec or code files — instruction-only. This is the lowest-risk install model: nothing is written to disk by an installer per the provided package metadata.
Credentials
Only a single credential (NEMO_TOKEN) is declared as required and used for API Bearer authentication. The instructions also describe generating a short-lived anonymous token via the service's anonymous endpoint when a token is not present. No other unrelated secrets or environment variables are requested.
Persistence & Privilege
The skill does not request persistent/always-on privileges (always:false). It instructs saving a session_id for the render workflow, which is normal for a session-based cloud service. It does not ask to modify other skills or global agent settings.
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 jianying-editor
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /jianying-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 Jianying Editor skill. - Instantly edit and export video clips with simple text instructions—no editing experience needed. - Supports uploading raw video footage (MP4, MOV, AVI, MKV, up to 500MB) and delivers AI-edited 1080p MP4s. - Automatic cloud-based processing with live status updates and session handling. - Easy workflow actions: upload, edit, preview, export, and track usage credits. - Designed for TikTok creators seeking fast, high-quality video edits without complex tools.
元数据
Slug jianying-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

Jianying Editor 是什么?

Get edited video clips ready to post, without touching a single slider. Upload your raw video footage (MP4, MOV, AVI, MKV, up to 500MB), say something like "... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 41 次。

如何安装 Jianying Editor?

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

Jianying Editor 是免费的吗?

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

Jianying Editor 支持哪些平台?

Jianying 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 Jianying Editor?

由 dsewell-583h0(@dsewell-583h0)开发并维护,当前版本 v1.0.0。

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