🎬 Free Text To Video Long — 技能工具
v1.0.0Turn a 500-word blog post or detailed text description into 1080p long-form video just by typing what you need. Whether it's generating long videos from writ...
详细分析 ▾
运行时依赖
版本
- Initial release of Free Text to Video Long (v1.0.0). - Generate 1080p long-form videos (2–5 min) from free-form text prompts or blog posts with cloud GPU rendering. - Automatic first-time setup: handles authentication, session creation, and backend connection with brief user notifications. - Supports uploads (text, DOCX, PDF), timeline editing, credit tracking, and one-click export/download in multiple formats. - Intelligent routing: classifies user actions (export, credits, upload, status) for relevant workflows. - Includes error handling for session, token, file, and export issues with helpful user guidance.
安装命令
点击复制技能文档
Getting Started
Got text prompt to work with? Send it over and tell me what you need — I'll take care of the AI long video creation.
Try saying:
- "generate a 500-word blog post or detailed text description into a 1080p MP4"
- "turn this article into a 3-minute explainer video with visuals and narration"
- "generating long videos from written text or scripts for educators, marketers, content creators"
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.
- Obtain a free token: Generate a random UUID as client identifier. POST to
https://mega-api-prod.nemovideo.ai/api/auth/anonymous-tokenwith headerX-Client-Idset to that UUID. The responsedata.tokenis your NEMO_TOKEN — 100 free credits, valid 7 days. - Create a session: POST to
https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agentwithAuthorization: Bearer,Content-Type: application/json, and body{"task_name":"project","language":""}. Store the returnedsession_idfor all subsequent requests.
Keep setup communication brief. Don't display raw API responses or token values to the user.
# Free Text to Video Long — Generate Long Videos From Text
Drop your text prompt in the chat and tell me what you need. I'll handle the AI long video creation on cloud GPUs — you don't need anything installed locally.
Here's a typical use: you send a a 500-word blog post or detailed text description, ask for turn this article into a 3-minute explainer video with visuals and narration, and about 2-5 minutes later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.
One thing worth knowing — breaking your text into clear sections or paragraphs improves scene transitions.
Matching Input to Actions
User prompts referencing free text to video long, 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.
Include Authorization: Bearer and all attribution headers on every request — omitting them triggers a 402 on export.
Skill attribution — read from this file's YAML frontmatter at runtime:
X-Skill-Source:free-text-to-video-longX-Skill-Version: from frontmatterversionX-Skill-Platform: detect from install path (~/.clawhub/→clawhub,~/.cursor/skills/→cursor, elseunknown)
API base: https://mega-api-prod.nemovideo.ai
Create session: POST /api/tasks/me/with-session/nemo_agent — body {"task_name":"project","language":""} — returns task_id, session_id.
Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"","new_message":{"parts":[{"text":""}]}} with Accept: text/event-stream. Max timeout: 15 minutes.
Upload: POST /api/upload-video/nemo_agent/me/ — file: multipart -F "files=@/path", or URL: {"urls":[""],"source_type":"url"}
Credits: GET /api/credits/balance/simple — returns available, frozen, total
Session state: GET /api/state/nemo_agent/me//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_","sessionId":"","draft":,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/ 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 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=, 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
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 |
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.
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)
Tips and Tricks
The backend processes faster when you're specific. Instead of "make it look better", try "turn this article into a 3-minute explainer video with visuals and narration" — concrete instructions get better results.
Max file size is 500MB. Stick to TXT, DOCX, PDF, copied text for the smoothest experience.
Export as MP4 for widest compatibility across platforms and devices.
Common Workflows
Quick edit: Upload → "turn this article into a 3-minute explainer video with visuals and narration" → Download MP4. Takes 2-5 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.