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francemichaell-15

Editing Generator

作者 francemichaell-15 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install editing-generator
功能描述
Turn a 3-minute unedited screen recording into 1080p edited video clips just by typing what you need. Whether it's automatically editing raw footage into a f...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "edit my raw video footage"
  • "export 1080p MP4"
  • "cut the pauses, add transitions, and"

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.

Editing Generator — Generate Edited Videos from Footage

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

Say you have a 3-minute unedited screen recording and want to cut the pauses, add transitions, and export a clean final video — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter clips under 2 minutes process significantly faster.

Matching Input to Actions

User prompts referencing editing generator, 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.

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

  • X-Skill-Source: editing-generator
  • 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.

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.

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)

Common Workflows

Quick edit: Upload → "cut the pauses, add transitions, and export a clean final 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "cut the pauses, add transitions, and export a clean final video" — 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 platforms.

安全使用建议
This skill appears to do what it claims: upload user-provided media to an external nemovideo service and return edited exports. Before installing, consider: (1) You will need to provide a NEMO_TOKEN (or allow the skill to obtain an anonymous token) — that token grants the service access to uploaded media, so only use a token from a trusted source. (2) Uploaded videos and audio will leave your device and be processed by https://mega-api-prod.nemovideo.ai — review the service's privacy/retention policy before sending sensitive content. (3) There is a minor metadata mismatch about an optional local config path (~/.config/nemovideo/); ask the publisher whether the skill will read that directory and why. (4) If you do not want the skill to upload files at all, do not provide a token or upload files. If anything about the domain, token issuance, or config access looks unfamiliar, request more publisher information or avoid installing.
功能分析
Type: OpenClaw Skill Name: editing-generator Version: 1.0.0 The skill is a legitimate integration for the NemoVideo AI video editing service, facilitating automated video processing through a cloud-based pipeline. It defines a clear workflow in SKILL.md for session management, file uploads, and rendering via the backend API at mega-api-prod.nemovideo.ai. The instructions guide the agent to handle authentication using the NEMO_TOKEN environment variable or an anonymous token and include logic for mapping user intents to specific API actions without any evidence of data exfiltration, malicious execution, or harmful prompt injection.
能力评估
Purpose & Capability
The skill is an instruction-only cloud video editor and requests a single API credential (NEMO_TOKEN), which matches the described cloud API usage. One inconsistency: the registry metadata supplied earlier listed no required config paths, but the SKILL.md frontmatter metadata lists a configPaths value (~/.config/nemovideo/). Requiring a token and optional local config for a cloud editing service is plausible, but the mismatch between sources should be clarified.
Instruction Scope
The SKILL.md confines actions to contacting the external nemovideo API, uploading user-supplied media, creating sessions, streaming SSE, polling render status, and returning download URLs. It does instruct the agent to read this file's YAML frontmatter (for attribution headers) and to detect an install path (to set X-Skill-Platform). Those filesystem reads are limited and explicable for attribution, not broad system data collection. There are no instructions to read unrelated environment variables, shell history, or other sensitive system files.
Install Mechanism
No install spec or code files are present; the skill is instruction-only so nothing is written to disk by an installer. This is the lowest-risk install profile.
Credentials
Only one primary credential (NEMO_TOKEN) is requested, which is proportionate for a cloud API. The skill also documents the ability to obtain an anonymous token from the service when NEMO_TOKEN is absent. The SKILL.md metadata referencing a local config path (~/.config/nemovideo/) suggests optional local config access; this was not listed in the registry summary earlier — clarify whether reading that config path is necessary.
Persistence & Privilege
The skill does not request permanent presence (always is false) and does not ask to modify other skills or global agent settings. Autonomous invocation is allowed by default (platform behavior) but not combined with other high-privilege requests.
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 editing-generator
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /editing-generator 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 — AI-powered video editing from raw footage to final export, all by chat. - Upload unedited video, describe your edits, and receive a 1080p edited download in 1–2 minutes. - Automatic session and token management with support for free trial credits. - Handles video/audio uploads, real-time editing prompts, export, and credit/status queries. - Tracks timeline state and summarizes edits, even if the backend response is silent. - Error messages and workflow tips ensure ease of use; supports multiple file types and batch edits.
元数据
Slug editing-generator
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

Editing Generator 是什么?

Turn a 3-minute unedited screen recording into 1080p edited video clips just by typing what you need. Whether it's automatically editing raw footage into a f... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 68 次。

如何安装 Editing Generator?

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

Editing Generator 是免费的吗?

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

Editing Generator 支持哪些平台?

Editing Generator 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 Editing Generator?

由 francemichaell-15(@francemichaell-15)开发并维护,当前版本 v1.0.0。

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