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Generator Green Screen

作者 whitejohnk-26 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install generator-green-screen
功能描述
generate video clips into green screen footage with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. video editors, content creators, YouTubers...
使用说明 (SKILL.md)

Getting Started

Share your video clips and I'll get started on green screen generation. Or just tell me what you're thinking.

Try saying:

  • "generate my video clips"
  • "export 1080p MP4"
  • "replace the background with a green"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

  1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
  2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer \x3Ctoken>, Content-Type: application/json, and body {"task_name":"project","language":"\x3Cdetected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

Generator Green Screen — Generate Green Screen Video Footage

Send me your video clips and describe the result you want. The green screen generation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 30-second talking head video clip, type "replace the background with a green screen so I can key it out in my editor", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: solid, evenly lit backgrounds produce the cleanest green screen output.

Matching Input to Actions

User prompts referencing generator green screen, 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: generator-green-screen
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else 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.

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 → "replace the background with a green screen so I can key it out in my editor" → Download MP4. Takes 30-60 seconds 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 "replace the background with a green screen so I can key it out in my editor" — 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 with editing software like Premiere and DaVinci.

安全使用建议
This skill appears purpose-aligned for cloud green-screen video generation. Before installing, be comfortable with sending your media and prompts to the NemoVideo API, using or generating a NEMO_TOKEN, and relying on remote render jobs that may consume credits or continue briefly if interrupted.
功能分析
Type: OpenClaw Skill Name: generator-green-screen Version: 1.0.0 The skill is a video processing tool that interfaces with a remote API at `mega-api-prod.nemovideo.ai`. It handles authentication via a dedicated environment variable (`NEMO_TOKEN`) or an anonymous token generation process. The instructions in `SKILL.md` are well-defined, focused on the stated purpose of green screen generation, and include security-conscious directions to avoid leaking tokens to the user.
能力评估
Purpose & Capability
The stated purpose is green-screen video generation, and the artifacts consistently describe uploading media to a cloud GPU service and returning an MP4. This is purpose-aligned, but it involves third-party processing of user media.
Instruction Scope
The skill gives the agent instructions to call specific NemoVideo API endpoints, handle SSE responses, upload files, check credits/state, and start exports. These actions are bounded to the video-rendering workflow, but users should expect network calls.
Install Mechanism
There is no install script or local code; this is an instruction-only skill. No local executable behavior or package-install risk is shown in the supplied artifacts.
Credentials
The required NEMO_TOKEN and external API calls are proportionate to a cloud rendering integration, but private videos, images, audio, and prompts may leave the local environment.
Persistence & Privilege
The skill creates remote sessions and render jobs, and notes that jobs can become orphaned if the tab closes. This appears tied to rendering rather than hidden persistence.
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 generator-green-screen
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /generator-green-screen 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
generator-green-screen 1.0.0 — Initial Release - Generate green screen video footage from MP4, MOV, AVI, and WebM files up to 500MB. - Upload video clips and receive processed 1080p MP4 files with green backgrounds, ready for editing. - All processing is cloud-based; setup includes automatic token and session management. - Supports basic prompt-based editing, batch processing, previews, and exporting. - File uploads, credit checks, and status queries are mapped to intuitive user prompts. - Provides clear error messages and summarizes editing operations for a seamless workflow.
元数据
Slug generator-green-screen
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

Generator Green Screen 是什么?

generate video clips into green screen footage with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. video editors, content creators, YouTubers... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 58 次。

如何安装 Generator Green Screen?

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

Generator Green Screen 是免费的吗?

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

Generator Green Screen 支持哪些平台?

Generator Green Screen 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 Generator Green Screen?

由 whitejohnk-26(@whitejohnk-26)开发并维护,当前版本 v1.0.0。

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