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...

Security Scan

The skill appears to implement a video-generation backend integration, but there are mismatches and vague instructions around credential handling, metadata vs. registry fields, and where tokens/sessions are stored — clarify before trusting with files or credentials.

Purpose & Capability

Name/description match a remote video-rendering backend (nemovideo.ai). However the registry declares NEMO_TOKEN as a required env var while the SKILL.md explicitly describes automatically obtaining an anonymous token when no NEMO_TOKEN is present. SKILL.md also includes a configPaths entry (~/.config/nemovideo/) in its frontmatter but the registry metadata lists no required config paths — this mismatch is inconsistent.

Instruction Scope

Instructions explicitly instruct the agent to POST to external endpoints, upload user media, stream SSE responses, and store session_id/token for subsequent calls — all expected for a cloud render service. It also instructs not to display raw tokens. The doc asks to auto-generate anonymous tokens if none provided, which expands the agent's authority (network calls that create credentials) and is not explicit about persistent storage location.

Install Mechanism

No install spec or code files; instruction-only skill means nothing is written to disk by an installer. This lowers risk from arbitrary installs.

Credentials

Only one credential (NEMO_TOKEN) is declared which is appropriate for the described API, but the SKILL.md's ability to auto-obtain a token reduces the need for NEMO_TOKEN and conflicts with the registry's 'required env var' claim. The frontmatter's configPaths hint that the skill might read/write a local configuration directory (~/.config/nemovideo/), but the registry did not list this — an unexplained request for local config access.

Persistence & Privilege

The skill does not request always:true and has no install. It does instruct storing session_id/token for subsequent requests and suggests a config path in frontmatter; it's unclear whether those values are kept ephemeral or persisted on disk — clarify where session/token are saved if persistence matters to you.

What to consider before installing

This skill will send your uploaded media and text prompts to a third-party service (mega-api-prod.nemovideo.ai) and either use an environment NEMO_TOKEN or create an anonymous token for you. Before installing, confirm: (1) you trust the nemovideo.ai domain to receive your files and any personal data, (2) whether the skill will persist tokens/session IDs on disk (the SKILL.md mentions ~/.config/nemovideo/ in frontmatter but the registry omitted it), and (3) why the registry requires NEMO_TOKEN if the skill can auto-generate anonymous tokens. If you handle sensitive content, avoid using this skill until the publisher provides a source/homepage, privacy policy, and a clear statement about where credentials/sessions are stored and how long uploads are retained.

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...	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":"<lang>"}. 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/<sid>	POST	Upload a file (multipart) or URL.
/api/credits/balance/simple	GET	Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/<sid>/latest	GET	Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda	POST	Start 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:

Header	Value
X-Skill-Source	free-video-generation-ai-models
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-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

Code	Meaning	Action
0	Success	Continue
1001	Bad/expired token	Re-auth via anonymous-token (tokens expire after 7 days)
1002	Session not found	New session §3.0
2001	No credits	Anonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001	Unsupported file	Show supported formats
4002	File too large	Suggest compress/trim
400	Missing X-Client-Id	Generate Client-Id and retry (see §1)
402	Free plan export blocked	Subscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429	Rate limit (1 token/client/7 days)	Retry in 30s once

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.

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

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.