Text To Video Google Flow
/install text-to-video-google-flow
Getting Started
Send me your text prompts and I'll handle the AI video generation. Or just describe what you're after.
Try saying:
- "generate a two-sentence description of a sunset over the ocean into a 1080p MP4"
- "generate a 10-second cinematic video clip from this text description"
- "generating short video clips from written text descriptions for marketers, content creators, educators"
Quick Start Setup
This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").
Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:
- Generate a UUID as client identifier
- POST
https://mega-api-prod.nemovideo.ai/api/auth/anonymous-tokenwithX-Client-Idheader - Extract
data.tokenfrom the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)
Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.
Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.
Text to Video Google Flow — Generate Videos from Text
Drop your text prompts in the chat and tell me what you need. I'll handle the AI video generation on cloud GPUs — you don't need anything installed locally.
Here's a typical use: you send a a two-sentence description of a sunset over the ocean, ask for generate a 10-second cinematic video clip from this text description, and about 1-3 minutes later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.
One thing worth knowing — shorter, more specific prompts produce more accurate and consistent video output.
Matching Input to Actions
User prompts referencing text to video google flow, 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.
Headers are derived from this file's YAML frontmatter. X-Skill-Source is text-to-video-google-flow, X-Skill-Version comes from the version field, and X-Skill-Platform is detected from the install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, otherwise unknown).
Include Authorization: Bearer \x3CNEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.
Error Codes
0— success, continue normally1001— token expired or invalid; re-acquire via/api/auth/anonymous-token1002— session not found; create a new one2001— out of credits; anonymous users get a registration link with?bind=\x3Cid>, registered users top up4001— unsupported file type; show accepted formats4002— file too large; suggest compressing or trimming400— missingX-Client-Id; generate one and retry402— free plan export blocked; not a credit issue, subscription tier429— rate limited; wait 30s and retry once
Reading the SSE Stream
Text events go straight to the user (after GUI translation). Tool calls stay internal. Heartbeats and empty data: lines mean the backend is still working — show "⏳ Still working..." every 2 minutes.
About 30% of edit operations close the stream without any text. When that happens, poll /api/state to confirm the timeline changed, then tell the user what was updated.
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 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)
Tips and Tricks
The backend processes faster when you're specific. Instead of "make it look better", try "generate a 10-second cinematic video clip from this text description" — concrete instructions get better results.
Max file size is 500MB. Stick to TXT, DOCX, PDF, plain text for the smoothest experience.
Export as MP4 for widest compatibility across platforms and devices.
Common Workflows
Quick edit: Upload → "generate a 10-second cinematic video clip from this text description" → Download MP4. Takes 1-3 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.
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install text-to-video-google-flow - After installation, invoke the skill by name or use
/text-to-video-google-flow - Provide required inputs per the skill's parameter spec and get structured output
What is Text To Video Google Flow?
Get AI-generated video ready to post, without touching a single slider. Upload your text prompts (TXT, DOCX, PDF, plain text, up to 500MB), say something lik... It is an AI Agent Skill for Claude Code / OpenClaw, with 42 downloads so far.
How do I install Text To Video Google Flow?
Run "/install text-to-video-google-flow" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Text To Video Google Flow free?
Yes, Text To Video Google Flow is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Text To Video Google Flow support?
Text To Video Google Flow is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Text To Video Google Flow?
It is built and maintained by francemichaell-15 (@francemichaell-15); the current version is v1.0.0.