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Editorial Highlight

作者 tk8544-b · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install editorial-highlight
功能描述
extract raw video footage into compiled highlight reel with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. video editors, journalists, content...
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:

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

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.

Editorial Highlight — Extract and Export Key Moments

Drop your raw video footage in the chat and tell me what you need. I'll handle the AI highlight extraction on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 30-minute interview or event recording, ask for pull the best moments and compile them into a 2-minute editorial highlight reel, 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 — the cleaner your source audio, the more accurately AI detects meaningful moments.

Matching Input to Actions

User prompts referencing editorial highlight, 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: editorial-highlight
  • 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)

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

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.

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 → "pull the best moments and compile them into a 2-minute editorial 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 "pull the best moments and compile them into a 2-minute editorial 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.

安全使用建议
This skill appears to do what it says (upload video, call a cloud render API, return a highlight reel), but there are a few things to check before installing: 1) Confirm the API domain (mega-api-prod.nemovideo.ai) and the service operator — there's no homepage or publisher info in the registry. 2) Understand privacy: any video you drop in chat will be sent to that external service; do not upload sensitive or confidential footage. 3) Clarify the config-path/inode behavior: the SKILL.md references ~/.config/nemovideo/ and probing install paths for X-Skill-Platform — ask whether the agent will read local filesystem paths and why. 4) Prefer supplying your own NEMO_TOKEN from a trusted account rather than relying on anonymous tokens if you care about billing/auditability. 5) Because the agent can invoke this skill autonomously, limit usage or vet triggers if you don't want uploads to happen without explicit confirmation. If the publisher can be identified and privacy/billing policies reviewed, the inconsistencies are explainable; otherwise treat the skill with caution.
功能分析
Type: OpenClaw Skill Name: editorial-highlight Version: 1.0.0 The skill is a functional integration for a cloud-based video editing service (nemovideo.ai). It provides instructions for an AI agent to manage authentication, session state, and video processing tasks via a specific API. While it requires a token and access to a local config directory (~/.config/nemovideo/), these are scoped to the service's functionality and no evidence of data exfiltration, malicious execution, or harmful prompt injection was found in SKILL.md or _meta.json.
能力评估
Purpose & Capability
The skill declares a single required credential (NEMO_TOKEN) and its runtime instructions call a single external API (mega-api-prod.nemovideo.ai) to perform GPU rendering — this aligns with a cloud video-processing highlight tool. However the SKILL.md metadata includes a config path (~/.config/nemovideo/) and install-path detection logic (for X-Skill-Platform) that are not reflected in the registry summary (which listed no required config paths). That mismatch is an inconsistency that should be clarified.
Instruction Scope
The SKILL.md instructs the agent to upload user-provided raw video files to an external service and to create/refresh tokens via an anonymous-token endpoint. Uploading potentially sensitive media to a third-party API is expected for this skill's function, but it is a significant privacy and exfiltration surface — users must consent. The instructions also direct the agent to inspect its install path to populate X-Skill-Platform attribution headers (reads local path), which is broader filesystem awareness than strictly necessary for editing operations.
Install Mechanism
This is an instruction-only skill with no install spec and no code files, so nothing is written to disk by an installer. That is the lowest-risk install model.
Credentials
Only NEMO_TOKEN is declared as required (primary credential), which is proportionate for a cloud API client. The SKILL.md also references a config directory (~/.config/nemovideo/) in its frontmatter metadata; it's unclear whether the agent will attempt to read that path at runtime. If it does, that expands the scope of credentials/config access and should be justified.
Persistence & Privilege
The skill does not request always:true and does not ask to modify other skills or system settings. It instructs saving session_id for its own sessions (normal). Autonomous invocation is allowed (default) — not flagged in isolation but increases blast radius if combined with other issues.
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 editorial-highlight
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /editorial-highlight 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
Editorial Highlight Skill v1.0.0 - Initial release: Extract key moments from raw video footage and export curated highlight reels. - Supports MP4, MOV, AVI, WebM files up to 500MB with 1080p output by default. - Cloud GPU processing delivers highlight edits within 1-2 minutes; outputs MP4 files. - Seamless integration: upload files, issue commands, receive curated highlight clips, and download results. - Automatic setup with free token generation if needed; credits system with balance checks. - Robust error handling, session management, and support for common editing workflows.
元数据
Slug editorial-highlight
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

Editorial Highlight 是什么?

extract raw video footage into compiled highlight reel with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. video editors, journalists, content... 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 Editorial Highlight?

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

Editorial Highlight 是免费的吗?

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

Editorial Highlight 支持哪些平台?

Editorial Highlight 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 Editorial Highlight?

由 tk8544-b(@tk8544-b)开发并维护,当前版本 v1.0.0。

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