Free Text No
/install free-text-no
Getting Started
Share your text prompts and I'll get started on AI video creation. Or just tell me what you're thinking.
Try saying:
- "generate my text prompts"
- "export 1080p MP4"
- "create a 30-second video from this"
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.
Free Text No — Generate Videos From Text Only
Drop your text prompts in the chat and tell me what you need. I'll handle the AI video creation on cloud GPUs — you don't need anything installed locally.
Here's a typical use: you send a a written description of a product demo scene, ask for create a 30-second video from this script without any uploaded footage, and about 1-2 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 results than vague long descriptions.
Matching Input to Actions
User prompts referencing free text no, 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.
All calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:
- Session —
POST /api/tasks/me/with-session/nemo_agentwith{"task_name":"project","language":"\x3Clang>"}. Gives you asession_id. - Chat (SSE) —
POST /run_ssewithsession_idand your message innew_message.parts[0].text. SetAccept: text/event-stream. Up to 15 min. - Upload —
POST /api/upload-video/nemo_agent/me/\x3Csid>— multipart file or JSON with URLs. - Credits —
GET /api/credits/balance/simple— returnsavailable,frozen,total. - State —
GET /api/state/nemo_agent/me/\x3Csid>/latest— current draft and media info. - Export —
POST /api/render/proxy/lambdawith render ID and draft JSON. PollGET /api/render/proxy/lambda/\x3Cid>every 30s forcompletedstatus and download URL.
Formats: 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 free-text-no, 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).
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.
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)
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.
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
Tips and Tricks
The backend processes faster when you're specific. Instead of "make it look better", try "create a 30-second video from this script without any uploaded footage" — concrete instructions get better results.
Max file size is 500MB. Stick to MP4, MOV, WebM, GIF for the smoothest experience.
Export as MP4 for widest compatibility.
Common Workflows
Quick edit: Upload → "create a 30-second video from this script without any uploaded footage" → 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.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install free-text-no - 安装完成后,直接呼叫该 Skill 的名称或使用
/free-text-no触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Free Text No 是什么?
Turn a written description of a product demo scene into 1080p text-generated videos just by typing what you need. Whether it's generating videos from text wi... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 41 次。
如何安装 Free Text No?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install free-text-no」即可一键安装,无需额外配置。
Free Text No 是免费的吗?
是的,Free Text No 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Free Text No 支持哪些平台?
Free Text No 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 Free Text No?
由 peandrover adam(@peand-rover)开发并维护,当前版本 v1.0.0。