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peand-rover

Free Text No

by peandrover adam · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install free-text-no
Description
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...
README (SKILL.md)

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-token with X-Client-Id header
  • Extract data.token from 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:

  1. SessionPOST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"\x3Clang>"}. Gives you a session_id.
  2. Chat (SSE)POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.
  3. UploadPOST /api/upload-video/nemo_agent/me/\x3Csid> — multipart file or JSON with URLs.
  4. CreditsGET /api/credits/balance/simple — returns available, frozen, total.
  5. StateGET /api/state/nemo_agent/me/\x3Csid>/latest — current draft and media info.
  6. ExportPOST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/\x3Cid> every 30s for completed status 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 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

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.

Usage Guidance
Install only if you are comfortable sending video prompts and any selected media to Nemo's cloud service. Use a limited-purpose token, watch credit usage, and ask the agent to confirm before exporting if the request is ambiguous.
Capability Analysis
Type: OpenClaw Skill Name: free-text-no Version: 1.0.0 The 'free-text-no' skill is a functional integration for the NemoVideo AI text-to-video service. It manages authentication by fetching anonymous tokens or using a provided 'NEMO_TOKEN', handles session state, and facilitates video rendering via the 'mega-api-prod.nemovideo.ai' backend. The instructions in 'SKILL.md' are well-defined for the agent to perform API calls, poll for job completion, and handle SSE streams without any evidence of data exfiltration, unauthorized command execution, or malicious prompt injection.
Capability Assessment
Purpose & Capability
The requested cloud rendering, SSE chat workflow, export polling, and optional upload handling match the stated AI video-generation purpose.
Instruction Scope
The skill tells the agent to translate backend GUI-style responses into API actions, including export actions, which is purpose-aligned but should remain user-directed when credits or downloads are involved.
Install Mechanism
There is no install spec and no code files; the artifact is instruction-only.
Credentials
Use of NEMO_TOKEN and calls to the Nemo cloud API are expected for this service, and the artifacts disclose the backend host and main endpoints.
Persistence & Privilege
The artifact keeps a session_id for operations but does not instruct persistent local storage, background agents, privileged system access, or long-running local services.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install free-text-no
  3. After installation, invoke the skill by name or use /free-text-no
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of Free Text No skill (v1.0.0) for generating 1080p videos from written text prompts only. - Supports seamless cloud setup, with auto-connection and token handling for new and returning users. - Processes user requests for video generation, export, credits, state, and uploads using a streamlined, chat-driven workflow. - Fast cloud rendering pipeline delivers MP4s and common video/audio/image formats within 1-2 minutes. - Robust session and error handling ensures a smooth user experience, including automatic recovery from token/session issues. - Includes detailed usage tips and guides for best results and efficient editing workflows.
Metadata
Slug free-text-no
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Free Text No?

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... It is an AI Agent Skill for Claude Code / OpenClaw, with 41 downloads so far.

How do I install Free Text No?

Run "/install free-text-no" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Free Text No free?

Yes, Free Text No is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Free Text No support?

Free Text No is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Free Text No?

It is built and maintained by peandrover adam (@peand-rover); the current version is v1.0.0.

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