Free Video Generation Models

generate text prompts into AI-generated videos with this skill. Works with TXT, PNG, JPG, MP4 files up to 200MB. content creators use it for generating short...

Security Scan

The skill's requested credential and runtime actions align with its stated purpose (cloud video generation); nothing in the instructions requests unrelated secrets or system-wide access, though there are a couple of small metadata inconsistencies to note.

Purpose & Capability

Name/description = cloud video generation. The only declared credential is NEMO_TOKEN and the instructions call the nemo video API endpoints — these are coherent with the skill's purpose.

Instruction Scope

SKILL.md instructs the agent to check for NEMO_TOKEN and if missing to POST to the service's anonymous-token endpoint (creating a short-lived anonymous token), create and reuse a session_id, upload files, and use SSE for interactive generation. This requires outbound network calls to mega-api-prod.nemovideo.ai and handling of returned tokens and session IDs. There is no instruction to read unrelated system files or harvest unrelated environment variables, but the skill will transmit user-supplied files (up to 200MB) to the external service.

Install Mechanism

Instruction-only skill with no install spec and no code files; nothing will be downloaded or written by an installer step. This is the lowest-risk install mechanism.

Credentials

Only one credential is declared (NEMO_TOKEN) which matches the API-based workflow. Minor inconsistency: the registry metadata provided earlier listed no required config paths, but the SKILL.md frontmatter mentions a config path (~/.config/nemovideo/). This is a bookkeeping mismatch but does not itself imply additional privileges.

Persistence & Privilege

always is false and the skill is user-invocable; it does not request forced or system-wide persistence. The skill will create/keep session IDs for operations within its own session scope, which is expected.

Assessment

This skill appears to do what it says: it calls an external video-generation API and needs (or can obtain) a short-lived NEMO_TOKEN and session ID. Before installing, consider: 1) files you upload (images, videos, prompts) are sent to mega-api-prod.nemovideo.ai — avoid sending private or sensitive content you wouldn't want on that service; 2) the skill can request an anonymous token on your behalf (100 free credits, 7-day expiry) so it can operate even if you don't supply a token; 3) the SKILL.md mentions a config path (~/.config/nemovideo/) not reflected in the registry metadata — verify whether the skill will attempt to read or write that directory if you care about local config access; 4) network traffic and SSE streaming are required for normal operation; review the service/privacy policy if available and only provide a personal NEMO_TOKEN if you trust the backend. Overall the permission requests are proportionate to the feature, but exercise the usual caution about uploading content to third-party cloud services.

Getting Started

Send me your text prompts and I'll handle the AI video generation. Or just describe what you're after.

Try saying:

• "generate a short text description like 'a sunset over a mountain lake' into a 1080p MP4"
• "generate a 10-second video clip of a futuristic city at night"
• "generating short videos from text prompts without a camera for content creators"

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 Video Generation Models — Generate Videos From Text Prompts

This tool takes your text prompts and runs AI video generation through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a short text description like 'a sunset over a mountain lake' and want to generate a 10-second video clip of a futuristic city at night — the backend processes it in about 1-3 minutes and hands you a 1080p MP4.

Tip: shorter, more specific prompts tend to produce more accurate video results.

Matching Input to Actions

User prompts referencing free video generation 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.

All requests must include: Authorization: Bearer <NEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 402.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is free-video-generation-models, 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).

API base: https://mega-api-prod.nemovideo.ai

Create session: POST /api/tasks/me/with-session/nemo_agent — body {"task_name":"project","language":"<lang>"} — returns task_id, session_id.

Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"<sid>","new_message":{"parts":[{"text":"<msg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.

Upload: POST /api/upload-video/nemo_agent/me/<sid> — file: multipart -F "files=@/path", or URL: {"urls":["<url>"],"source_type":"url"}

Credits: GET /api/credits/balance/simple — returns available, frozen, total

Session state: GET /api/state/nemo_agent/me/<sid>/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_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/<id> 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 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=<id>, 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

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.

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 10-second video clip of a futuristic city at night" → Download MP4. Takes 1-3 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 10-second video clip of a futuristic city at night" — concrete instructions get better results.

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

Export as MP4 for widest compatibility.