free-video-generation-ai-models

Get AI generated videos ready to post, without touching a single slider. Upload your text prompts or images (MP4, MOV, PNG, JPG, up to 200MB), say something like "generate a 15-second video clip from my product description", and download 1080p MP4 when it's done. Built for content creators and marketers who move fast and want to create videos without filming or expensive tools.

Safety Notice

This listing is from the official public ClawHub registry. Review SKILL.md and referenced scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "free-video-generation-ai-models" with this command: npx skills add mhogan2013-9/free-video-generation-ai-models

Getting Started

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

Try saying:

  • "generate my text prompts or images"
  • "export 1080p MP4"
  • "generate a 15-second video clip from"

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.

  1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
  2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer <token>, Content-Type: application/json, and body {"task_name":"project","language":"<detected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

Free Video Generation AI Models — Generate Videos from Text or Images

Send me your text prompts or images 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 like 'a sunset over a mountain lake', type "generate a 15-second video clip from my product description", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter prompts with clear subjects produce more consistent results.

Matching Input to Actions

User prompts referencing free video generation ai models, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

User says...ActionSkip 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

EndpointMethodPurpose
/api/tasks/me/with-session/nemo_agentPOSTStart a new editing session. Body: {"task_name":"project","language":"<lang>"}. Returns session_id.
/run_ssePOSTSend 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/<sid>POSTUpload a file (multipart) or URL.
/api/credits/balance/simpleGETCheck remaining credits (available, frozen, total).
/api/state/nemo_agent/me/<sid>/latestGETFetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambdaPOSTStart export. Body: {"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"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.

Three attribution headers are required on every request and must match this file's frontmatter:

HeaderValue
X-Skill-Sourcefree-video-generation-ai-models
X-Skill-Versionfrontmatter version
X-Skill-Platformauto-detect: clawhub / cursor / unknown from install path

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

Error Handling

CodeMeaningAction
0SuccessContinue
1001Bad/expired tokenRe-auth via anonymous-token (tokens expire after 7 days)
1002Session not foundNew session §3.0
2001No creditsAnonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001Unsupported fileShow supported formats
4002File too largeSuggest compress/trim
400Missing X-Client-IdGenerate Client-Id and retry (see §1)
402Free plan export blockedSubscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429Rate limit (1 token/client/7 days)Retry in 30s once

SSE Event Handling

EventAction
Text responseApply GUI translation (§4), present to user
Tool call/resultProcess internally, don't forward
heartbeat / empty data:Keep waiting. Every 2 min: "⏳ Still working..."
Stream closesProcess 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.

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend saysYou 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

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)

Common Workflows

Quick edit: Upload → "generate a 15-second video clip from my product description" → 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 "generate a 15-second video clip from my product description" — concrete instructions get better results.

Max file size is 200MB. Stick to MP4, MOV, PNG, JPG for the smoothest experience.

Export as MP4 for widest compatibility.

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

General

Multi Edge-TTS CN

Edge-TTS 在线语音合成 skill。基于微软 Edge TTS 引擎,生成速度快(1-2秒),支持多种音色和输出格式。同时支持飞书(OGG/Opus)和企业微信(AMR)。默认音色 xiaoxiao_lively。需联网。

Registry SourceRecently Updated
General

vedic-destiny

吠陀命盘分析中文入口。用于完整命盘研判、命主盘 Rashi chart 与九分盘 Navamsha chart 联读、既往事件回看、出生时间稳定度判断、事业主题、婚姻主题、时空盘专题,以及基于 Jagannatha Hora PDF、星盘截图或文本命盘数据的系统拆盘。当用户提到完整星盘、事业方向、婚姻问题、关系窗...

Registry SourceRecently Updated
General

One Person Company OS

Build a visual operating cockpit for an AI-native one-person company across promise, buyer, product, delivery, cash, learning, and assets. / 为 AI 一人公司建立可视化经营...

Registry SourceRecently Updated
General

健康追踪

健康追踪技能 - 追踪饮水、睡眠、步数等健康数据,JSON存储。

Registry SourceRecently Updated