Ai Video Generation Free

Get AI generated videos ready to post, without touching a single slider. Upload your text prompts (MP4, MOV, WebM, AVI, up to 500MB), say something like "gen...

Security Scan

The skill mostly matches an AI video-generation helper, but there are inconsistencies in declared vs. documented requirements (config paths), unknown provenance, and instructions that imply filesystem probing for platform detection — so proceed with caution.

Purpose & Capability

Name and description (AI video generation) align with the documented endpoints and the single required credential (NEMO_TOKEN). However, the SKILL.md frontmatter declares a config path (~/.config/nemovideo/) while the registry metadata lists no required config paths — a mismatch that needs explanation.

Instruction Scope

Runtime instructions are concrete and limited to interacting with nemovideo.ai (auth, session, upload, SSE, render). But the SKILL.md instructs the agent to detect install platform by inspecting install paths (~/.clawhub/, ~/.cursor/skills/) and derives headers from the SKILL.md frontmatter; both behaviors imply the agent may probe filesystem paths outside the skill's immediate data. Also it instructs persisting session_id and using/setting NEMO_TOKEN — expected for the service, but confirm where/how session tokens are stored.

Install Mechanism

Instruction-only skill with no install spec and no bundled code; this minimizes local disk writes and makes the attack surface primarily network calls to the documented API.

Credentials

Only one credential is declared (NEMO_TOKEN), which is proportionate for a cloud API. But the SKILL.md frontmatter's configPaths (~/.config/nemovideo/) conflicts with registry reporting none, suggesting the skill may access that directory if present. Also platform-detection via install-path probing could reveal agent installation directories, which is not strictly necessary for video generation.

Persistence & Privilege

Skill is not 'always' enabled, has no install hooks, and does not request system-wide privileges. It does require storing session_id and uses tokens for API calls — normal for a client of a cloud service.

What to consider before installing

This skill appears to be a thin client for nemovideo.ai and asks only for NEMO_TOKEN — that's expected — but there are a few things to check before installing: - Provenance: the skill has no homepage and the source is unknown. Prefer packages with a clear owner, website, and docs. Ask the publisher where the service is hosted and verify the domain (mega-api-prod.nemovideo.ai) is legitimate. - Config path mismatch: SKILL.md mentions ~/.config/nemovideo/ while the registry says no config paths. Confirm whether the skill will read or write that directory and what it stores there (session IDs, tokens, logs). - Filesystem probing: the instructions say to detect platform from install paths (~/.clawhub/, ~/.cursor/skills/). If you want to avoid exposing your agent install layout, ask the publisher to remove or justify this behavior. It's not needed to call the video API. - Token handling: NEMO_TOKEN is the only credential requested. If you must set it, prefer a short-lived or scoped token. The skill also documents an anonymous-token flow; you can prefer that to avoid placing a long-lived token in your environment. - Network calls: the skill will make outbound HTTPS requests to the documented API and will send headers derived from the skill metadata. If you have strict data policies, confirm what user content is uploaded and retained. If you decide to proceed, request clearer documentation from the publisher about where session tokens are stored and why the skill needs to detect install paths. If you cannot verify the publisher or behavior, treat this as untrusted and avoid setting a long-lived NEMO_TOKEN in global environment variables.

Getting Started

Ready when you are. Drop your text prompts here or describe what you want to make.

Try saying:

• "generate a short text prompt describing a 30-second product promo into a 1080p MP4"
• "generate a 30-second video from my script about a coffee brand"
• "generating videos from text prompts without filming anything for content creators"

Automatic Setup

On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".

Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.

Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: <uuid>. The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).

Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.

Confirm to the user you're connected and ready. Don't print tokens or raw JSON.

AI Video Generation Free — Generate Videos from Text Prompts

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

Say you have a short text prompt describing a 30-second product promo and want to generate a 30-second video from my script about a coffee brand — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter prompts with clear scene descriptions produce more accurate results.

Matching Input to Actions

User prompts referencing ai video generation free, 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.

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

Include Authorization: Bearer <NEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

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

Reading the SSE Stream

Text events go straight to the user (after GUI translation). Tool calls stay internal. Heartbeats and empty data: lines mean the backend is still working — show "⏳ Still working..." every 2 minutes.

About 30% of edit operations close the stream without any text. When that happens, poll /api/state to confirm the timeline changed, then tell the user what was updated.

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 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)

Common Workflows

Quick edit: Upload → "generate a 30-second video from my script about a coffee brand" → 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 30-second video from my script about a coffee brand" — concrete instructions get better results.

Max file size is 500MB. Stick to MP4, MOV, WebM, AVI for the smoothest experience.

Export as MP4 for widest compatibility across social platforms.