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Generation To Generator

作者 mhogan2013-9 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install generation-to-generator
功能描述
Skip the learning curve of professional editing software. Describe what you want — turn this script into a 30-second video with visuals and music — and get A...
使用说明 (SKILL.md)

Getting Started

Share your text prompts and I'll get started on AI video generation. Or just tell me what you're thinking.

Try saying:

  • "generate my text prompts"
  • "export 1080p MP4"
  • "turn this script into a 30-second"

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.

Generation to Generator — Turn Text Into Generated Videos

Send me your text prompts and describe the result you want. The AI video generation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a short text description of a product launch scene, type "turn this script into a 30-second video with visuals and music", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter and more specific prompts produce more accurate video results.

Matching Input to Actions

User prompts referencing generation to 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.

Every API call needs Authorization: Bearer \x3CNEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

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

  • X-Skill-Source: generation-to-generator
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

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.

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

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

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.

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 → "turn this script into a 30-second video with visuals and music" → 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 "turn this script into a 30-second video with visuals and music" — concrete instructions get better results.

Max file size is 200MB. Stick to TXT, DOCX, PDF, MP4 for the smoothest experience.

Export as MP4 for widest compatibility.

安全使用建议
This skill appears purpose-aligned for cloud video generation. Before installing, confirm you trust NemoVideo and the API domain, use only an appropriate service token, and avoid uploading private documents or media unless you are comfortable with remote processing.
功能分析
Type: OpenClaw Skill Name: generation-to-generator Version: 1.0.0 The 'generation-to-generator' skill is a functional integration for a cloud-based AI video generation service (nemovideo.ai). The SKILL.md file provides detailed instructions for an AI agent to manage authentication (via NEMO_TOKEN or anonymous UUID-based tokens), handle file uploads, and interact with a remote rendering pipeline. It includes appropriate error handling and security-conscious instructions, such as suppressing the output of raw tokens or JSON. No indicators of data exfiltration, malicious execution, or harmful prompt injection were found.
能力评估
Purpose & Capability
Purpose and capability align: SKILL.md says video generation runs on remote GPU nodes and supports uploads, so remote processing is expected.
Instruction Scope
SKILL.md says to connect to the processing API on first interaction and translate some backend UI prompts into API actions; this is bounded to the video workflow but should be expected after invocation.
Install Mechanism
There is no install spec or code, but the registry lists Source: unknown and Homepage: none, so users have limited provenance information for the remote service integration.
Credentials
The required NEMO_TOKEN and optional anonymous token are purpose-aligned with the NemoVideo API, and the artifact explicitly says not to print tokens.
Persistence & Privilege
No local background worker or persistent code is shown; the artifact only saves a session_id for the active cloud render session.
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 generation-to-generator
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /generation-to-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 of Generation to Generator — Turn Text Into Generated Videos: - Instantly turn text prompts or scripts into AI-generated videos with visuals and music. - Supports uploads of TXT, DOCX, PDF, MP4 files up to 200MB for video processing. - Automatic setup with anonymous tokens for quick access; no manual authentication required. - Offers cloud-powered 1080p MP4 video rendering with a simple prompt-driven workflow. - Built-in actions for uploading files, checking credits, exporting videos, and managing session state. - Optimized for marketers and creators wanting fast, no-filming-required video generation from written content.
元数据
Slug generation-to-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

Generation To Generator 是什么?

Skip the learning curve of professional editing software. Describe what you want — turn this script into a 30-second video with visuals and music — and get A... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 36 次。

如何安装 Generation To Generator?

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

Generation To Generator 是免费的吗?

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

Generation To Generator 支持哪些平台?

Generation To 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 Generation To Generator?

由 mhogan2013-9(@mhogan2013-9)开发并维护,当前版本 v1.0.0。

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