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Ai Video Editor Montage

作者 mory128 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install ai-video-editor-montage
功能描述
Turn five 30-second travel clips into 1080p polished montage video just by typing what you need. Whether it's assembling multiple clips into a single edited...
使用说明 (SKILL.md)

Getting Started

Ready when you are. Drop your video clips here or describe what you want to make.

Try saying:

  • "create five 30-second travel clips into a 1080p MP4"
  • "cut these clips into a 60-second montage with transitions and music sync"
  • "assembling multiple clips into a single edited montage video for content creators"

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.

AI Video Editor Montage — Turn Clips Into Montage Videos

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

Here's a typical use: you send a five 30-second travel clips, ask for cut these clips into a 60-second montage with transitions and music sync, 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 clips give the AI more flexibility to build a tighter montage.

Matching Input to Actions

User prompts referencing ai video editor montage, 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 ai-video-editor-montage, 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).

All requests must include: Authorization: Bearer \x3CNEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 402.

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 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)

Common Workflows

Quick edit: Upload → "cut these clips into a 60-second montage with transitions and music sync" → 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "cut these clips into a 60-second montage with transitions and music sync" — 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 social platforms.

安全使用建议
This skill behaves like a normal cloud video editor: it uploads your clips to mega-api-prod.nemovideo.ai, creates sessions, and returns rendered MP4s. Things to consider before installing or invoking it: - Privacy: your videos and audio are sent to an external service—do not upload sensitive content unless you trust the domain and its terms. - Credentials: the skill uses a single NEMO_TOKEN; if you don't provide one it will request an anonymous token for you. If you prefer control, set your own token rather than relying on auto-generated anonymous tokens. - Transparency: the SKILL.md explicitly tells the agent to 'keep technical details out of the chat' (i.e., hide backend activity), which reduces visibility into what the skill is doing—ask for explicit confirmation/logs before uploads. - Local info leakage: the skill notes it will detect install paths to populate X-Skill-Platform headers—this may expose local path/platform details. - Authenticity: the homepage is unknown and the skill source is 'unknown'—verify the backend domain (mega-api-prod.nemovideo.ai) and the service's legitimacy before sending data. - Inconsistencies: there is a small metadata mismatch (config path in frontmatter vs registry metadata), which suggests the package may not have been carefully curated. If you decide to use it, prefer setting your own NEMO_TOKEN, avoid uploading sensitive footage, and request that the skill surface explicit upload/download URLs and logs in chat so you can verify actions.
功能分析
Type: OpenClaw Skill Name: ai-video-editor-montage Version: 1.0.0 The skill bundle provides a legitimate integration for an AI video editing service hosted at nemovideo.ai. It contains standard API interaction logic for session management, file uploads, and video rendering, including a fallback mechanism to acquire anonymous tokens. The instructions in SKILL.md are focused on guiding the agent through the video processing workflow and providing user feedback, with no evidence of data exfiltration, malicious execution, or harmful prompt injection.
能力评估
Purpose & Capability
Name/description (cloud montage editing) align with the declared primary credential NEMO_TOKEN and the SKILL.md which calls a nemo-video backend—requesting a single NEMO_TOKEN is proportionate. However, the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) that is not listed in the registry metadata, an internal mismatch worth noting.
Instruction Scope
Runtime instructions tell the agent to upload user video/audio files to https://mega-api-prod.nemovideo.ai, create sessions, poll rendering endpoints, and (if no NEMO_TOKEN) POST for an anonymous token by generating a UUID. Those network actions are expected for a cloud editor, but the skill also instructs the agent to 'Keep the technical details out of the chat' (discouraging transparency) and to detect the install path to set X-Skill-Platform (this requires inspecting local paths and may leak local environment info). Both of those are privacy/behavioral concerns.
Install Mechanism
Instruction-only skill with no install spec and no code files—lowest install risk. Nothing will be downloaded or written by an install step according to the provided metadata.
Credentials
Only NEMO_TOKEN is required (primaryEnv). That is proportionate to a cloud service API. Caveats: the SKILL.md will generate an anonymous token if NEMO_TOKEN is missing (so it can operate without user-supplied credentials), and it requests adding attribution headers derived from local install paths (which may expose local path information). The frontmatter's config path (~/.config/nemovideo/) is present but not declared in registry requirements—minor inconsistency.
Persistence & Privilege
always:false and default autonomous invocation are set. The skill does not request system-wide persistence or modify other skills. It does create short-lived session tokens with the backend, which is normal for this use case.
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 ai-video-editor-montage
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /ai-video-editor-montage 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 AI Video Editor Montage — quickly assemble and edit montage videos from your clips using cloud-based AI. - Instantly turn up to five 30-second video clips into a polished 1080p montage in 1–2 minutes. - Just upload your clips and describe the montage you want; no timeline editing or export settings needed. - Automatic connection to backend AI — handles anonymous tokens if needed and manages credits. - Supports smart actions for uploading, montage generation, export, checking credits, and session state with simple prompts. - Accepts common video, audio, and image formats up to 500MB per file; exports MP4 by default for sharing. - Robust error handling and helpful status updates ensure a smooth editing workflow.
元数据
Slug ai-video-editor-montage
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

Ai Video Editor Montage 是什么?

Turn five 30-second travel clips into 1080p polished montage video just by typing what you need. Whether it's assembling multiple clips into a single edited... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 67 次。

如何安装 Ai Video Editor Montage?

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

Ai Video Editor Montage 是免费的吗?

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

Ai Video Editor Montage 支持哪些平台?

Ai Video Editor Montage 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 Ai Video Editor Montage?

由 mory128(@mory128)开发并维护,当前版本 v1.0.0。

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