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Ai Video Editor Highlights

作者 peandrover adam · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install ai-video-editor-highlights
功能描述
Get highlight reel clips ready to post, without touching a single slider. Upload your raw video footage (MP4, MOV, AVI, WebM, up to 500MB), say something lik...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "generate my raw video footage"
  • "export 1080p MP4"
  • "extract the best moments and compile"

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 Highlights — Extract and Export Video Highlights

Send me your raw video footage and describe the result you want. The AI highlight extraction runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 90-minute sports game recording, type "extract the best moments and compile them into a 2-minute highlight reel", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: uploading footage with clear audio cues helps the AI detect highlights more accurately.

Matching Input to Actions

User prompts referencing ai video editor highlights, 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.

Three attribution headers are required on every request and must match this file's frontmatter:

Header Value
X-Skill-Source ai-video-editor-highlights
X-Skill-Version frontmatter version
X-Skill-Platform auto-detect: clawhub / cursor / unknown from install path

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.

API base: https://mega-api-prod.nemovideo.ai

Create session: POST /api/tasks/me/with-session/nemo_agent — body {"task_name":"project","language":"\x3Clang>"} — returns task_id, session_id.

Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"\x3Csid>","new_message":{"parts":[{"text":"\x3Cmsg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.

Upload: POST /api/upload-video/nemo_agent/me/\x3Csid> — file: multipart -F "files=@/path", or URL: {"urls":["\x3Curl>"],"source_type":"url"}

Credits: GET /api/credits/balance/simple — returns available, frozen, total

Session state: GET /api/state/nemo_agent/me/\x3Csid>/latest — key fields: data.state.draft, data.state.video_infos, data.state.generated_media

Export (free, no credits): POST /api/render/proxy/lambda — body {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/\x3Cid> every 30s until status = completed. Download URL at output.url.

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

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)

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

Common Workflows

Quick edit: Upload → "extract the best moments and compile them into a 2-minute highlight reel" → 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 "extract the best moments and compile them into a 2-minute highlight reel" — 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 appears to implement a cloud-based video highlight pipeline and will upload any videos you give it to https://mega-api-prod.nemovideo.ai for server-side processing. Before installing or using it: (1) Ask the publisher why NEMO_TOKEN is marked as required when the instructions describe an anonymous-token fallback — prefer anonymous tokens if you do not want a persistent credential stored in your environment. (2) Ask why the metadata lists a local config path (~/.config/nemovideo/) and whether the skill will read local files; do not grant or place credentials/configs there unless you trust the vendor. (3) Understand privacy/retention policies for uploaded videos and who can access them (retention time, sharing, processing). (4) Confirm the exact header/attribution behavior and whether any agent filesystem reads (install-path detection) are performed — if you want to avoid local filesystem access, require the vendor to remove install-path auto-detection. If the author provides code, a clear privacy policy, or removes the unexplained config-path requirement, my confidence would increase and the rating could change to benign.
功能分析
Type: OpenClaw Skill Name: ai-video-editor-highlights Version: 1.0.0 The skill acts as a legitimate interface for a cloud-based video editing service (nemovideo.ai). It manages authentication, session creation, and video processing via the 'https://mega-api-prod.nemovideo.ai' API. While it uploads user video data to remote GPU nodes and requires an API token (NEMO_TOKEN), these actions are transparently documented in SKILL.md and are essential for the stated functionality of AI-driven highlight extraction.
能力评估
Purpose & Capability
The skill's name and description match the runtime instructions: it uploads user videos to a remote API and returns rendered highlights. Requesting network access and a bearer token is consistent with that purpose. However, the registry metadata marks NEMO_TOKEN as a required primary credential while the SKILL.md provides an anonymous-token fallback flow — this is inconsistent.
Instruction Scope
Instructions are explicit about API endpoints, session creation, uploads, SSE handling, and export polling — all relevant to a remote video-editing service. They instruct creating a UUID, POSTing to auth and session endpoints, and uploading user files. The only scope concern is the requirement to auto-detect an "install path" to set X-Skill-Platform and the metadata's configPaths (~/.config/nemovideo/) — the doc doesn't show any legitimate need to read local config paths or the filesystem, so that is unclear.
Install Mechanism
Instruction-only skill with no install spec and no code files: nothing is written to disk by the skill itself. This is the lowest install risk.
Credentials
The only declared env var is NEMO_TOKEN, which is reasonable for an API-backed service. However, the SKILL.md itself supports getting an anonymous token if NEMO_TOKEN is absent, so marking NEMO_TOKEN as "required" in metadata is disproportionate. Additionally, the metadata declares a config path (~/.config/nemovideo/) but the instructions never explain reading it — requesting access to a user config path without justification is suspicious.
Persistence & Privilege
always:false and no install steps. The skill does not request permanent inclusion or system-wide changes. It will cause uploads of user video to a remote service (expected for function) but does not request elevated agent privileges.
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-highlights
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /ai-video-editor-highlights 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
AI Video Editor Highlights 1.0.0 — initial release. - Instantly extract and export video highlights using AI, with no manual editing. - Upload raw footage (MP4, MOV, AVI, WebM; up to 500MB), instruct the AI, and receive a compiled 1080p MP4 highlight reel. - Built for sports creators, event videographers, and YouTubers needing fast highlight extraction. - Simple session and token handling—automatic sign-in with a free starter token if needed. - Supports file upload, credits/balance checks, real-time session monitoring, and cloud-accelerated rendering.
元数据
Slug ai-video-editor-highlights
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 Highlights 是什么?

Get highlight reel clips ready to post, without touching a single slider. Upload your raw video footage (MP4, MOV, AVI, WebM, up to 500MB), say something lik... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 65 次。

如何安装 Ai Video Editor Highlights?

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

Ai Video Editor Highlights 是免费的吗?

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

Ai Video Editor Highlights 支持哪些平台?

Ai Video Editor Highlights 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 Highlights?

由 peandrover adam(@peand-rover)开发并维护,当前版本 v1.0.0。

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