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🎬 Scene Video

v1.0.0

Turn a 3-minute raw footage file with multiple locations into 1080p scene-cut video just by typing what you need. Whether it's splitting footage into scenes...

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License
MIT-0
最后更新
2026/4/12
安全扫描
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OpenClaw
可疑
medium confidence
The skill's behavior mostly fits a cloud video-editing service, but there are incoherences (metadata vs. runtime instructions) and the instructions ask the agent to probe local install paths/metadata — verify before installing or providing credentials.
评估建议
This skill looks like a legitimate cloud video-editing integrator, but there are red flags: (1) the SKILL.md claims it will read local config/install paths (to set an X-Skill-Platform header) while the published registry metadata you received does not list those config path requirements — ask the publisher to clarify and update registry metadata. (2) The skill will call an external API domain and can mint anonymous tokens; prefer using a limited-scope or throwaway NEMO_TOKEN if you want to test....
详细分析 ▾
用途与能力
The skill's name/description and required NEMO_TOKEN align with a cloud video-rendering service. However the SKILL.md frontmatter claims it will read a config path (~/.config/nemovideo/) and detect install paths to set X-Skill-Platform, while the registry metadata provided to you lists no required config paths — this mismatch is incoherent and could hide filesystem access not declared to the registry.
指令范围
Runtime instructions involve network calls to mega-api-prod.nemovideo.ai for auth, session creation, uploads, SSE, and rendering (expected), but they also instruct the agent to read the skill file's YAML frontmatter and to detect install paths (e.g., ~/.clawhub, ~/.cursor/skills) to set attribution headers. Detecting install path may require reading local filesystem or environment and is not clearly justified for the core video-editing task.
安装机制
Instruction-only skill with no install spec or code files — lowest install risk. There is no downloadable archive or third-party package to fetch.
凭证需求
Only one credential (NEMO_TOKEN) is declared and used, which is appropriate for a remote API. The skill can also mint an anonymous starter token via the public anonymous-token endpoint if NEMO_TOKEN is absent. The frontmatter's mention of configPaths (~/.config/nemovideo/) is not reflected in the registry metadata you were shown, creating an unexplained access claim.
持久化与权限
The skill is not marked always:true and uses normal autonomous invocation. It does not request persistent system-wide privileges in the provided instructions.
安全有层次,运行前请审查代码。

License

MIT-0

可自由使用、修改和再分发,无需署名。

运行时依赖

无特殊依赖

版本

latestv1.0.02026/4/12

Scene Video 1.0.0 — Initial Release - Instantly split and assemble 3-minute raw footage into 1080p scene-cut videos via simple text prompts. - Simply upload your clips, describe your desired outcome, and receive an export-ready MP4 within minutes—no editing software or manual timeline work needed. - Seamless backend setup: automatic session management and API connection, including free token generation for new users. - Supports multiple video, audio, and image formats up to 500MB file size. - Easily preview timeline, check credits, track render status, and handle common errors with clear messaging. - Optimized for fast social content, short film scenes, and batch or iterative editing workflows.

● 无害

安装命令 点击复制

官方npx clawhub@latest install scene-video
镜像加速npx clawhub@latest install scene-video --registry https://cn.clawhub-mirror.com

技能文档

Getting Started

Got video clips to work with? Send it over and tell me what you need — I'll take care of the AI scene assembly.

Try saying:

  • "create a 3-minute raw footage file with multiple locations into a 1080p MP4"
  • "split this footage into individual scenes and arrange them into a cohesive video"
  • "splitting footage into scenes and assembling them into a structured video for filmmakers, content creators, social media editors"

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

  • Generate a UUID as client identifier
  • POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
  • The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

# Scene Video — Split and Assemble Video Scenes

Drop your video clips in the chat and tell me what you need. I'll handle the AI scene assembly on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 3-minute raw footage file with multiple locations, ask for split this footage into individual scenes and arrange them into a cohesive 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 individual scenes under 30 seconds process and render significantly faster.

Matching Input to Actions

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

User says...ActionSkip 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

EndpointMethodPurpose
/api/tasks/me/with-session/nemo_agentPOSTStart a new editing session. Body: {"task_name":"project","language":""}. Returns session_id.
/run_ssePOSTSend 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/POSTUpload a file (multipart) or URL.
/api/credits/balance/simpleGETCheck remaining credits (available, frozen, total).
/api/state/nemo_agent/me//latestGETFetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambdaPOSTStart export. Body: {"id":"render_","sessionId":"","draft":,"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.

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

  • X-Skill-Source: scene-video
  • 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 plus the three attribution headers above. If any header is missing, exports return 402.

Error Handling

CodeMeaningAction
0SuccessContinue
1001Bad/expired tokenRe-auth via anonymous-token (tokens expire after 7 days)
1002Session not foundNew session §3.0
2001No creditsAnonymous: show registration URL with ?bind= (get from create-session or state response when needed). Registered: "Top up credits in your account"
4001Unsupported fileShow supported formats
4002File too largeSuggest compress/trim
400Missing X-Client-IdGenerate Client-Id and retry (see §1)
402Free plan export blockedSubscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429Rate limit (1 token/client/7 days)Retry in 30s once

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.

Translating GUI Instructions

The backend responds as if there's a visual interface. Map its instructions to API calls:

  • "click" or "点击" → execute the action via the relevant endpoint
  • "open" or "打开" → query session state to get the data
  • "drag/drop" or "拖拽" → send the edit command through SSE
  • "preview in timeline" → show a text summary of current tracks
  • "Export" or "导出" → run the 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 "split this footage into individual scenes and arrange them into a cohesive video" — concrete instructions get better results.

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

Export as MP4 with H.264 codec for the best balance of quality and file size.

Common Workflows

Quick edit: Upload → "split this footage into individual scenes and arrange them into a cohesive 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.

数据来源:ClawHub ↗ · 中文优化:龙虾技能库
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