Video Leonardo Ai

Skip the learning curve of professional editing software. Describe what you want — generate a 10-second cinematic video from this image of a forest at sunset...

Security Scan

The skill's code-free instructions, required token, and network endpoints are coherent with its stated purpose (cloud video generation); no disproportionate or unrelated requirements were found, but review privacy before uploading media and note a small metadata inconsistency.

Purpose & Capability

The skill advertises cloud AI video generation and its runtime instructions exclusively call a remote video-rendering API (session creation, SSE, uploads, render endpoints). Requiring a single service credential (NEMO_TOKEN) and providing an anonymous-token fallback are consistent with that purpose.

Instruction Scope

Instructions focus on the service API, upload flow, SSE, polling, and required headers — all expected. Two items to note: (1) the skill requires adding attribution headers on every request (X-Skill-Source/Version/Platform), and asks the agent to auto-detect install platform from an install path (this may require reading runtime/install metadata). (2) The SKILL.md instructs generating/using anonymous tokens if NEMO_TOKEN is absent, which is logical but means the agent will POST to an external auth endpoint and then reuse that token for subsequent requests.

Install Mechanism

There is no install spec and no code files — this is instruction-only, so nothing will be written to disk or automatically installed by the skill. That minimizes install-time risk.

Credentials

The skill only declares a single required env var (NEMO_TOKEN) which is appropriate for a cloud API client. However, the SKILL.md frontmatter includes a configPaths entry (~/.config/nemovideo/) while the registry metadata reported no required config paths — this inconsistency should be clarified. Otherwise no unrelated credentials are requested.

Persistence & Privilege

always is false and there is no install script. The skill can be invoked by the agent (normal default) but does not request permanent platform-wide privileges or modify other skills' configs.

Assessment

This skill is coherent for generating videos via a third‑party cloud service, but it will upload any images/media you give it to https://mega-api-prod.nemovideo.ai. Before installing or using: (1) Do not upload sensitive or proprietary images unless you trust the service and its privacy/retention policies. (2) Confirm the NEMO_TOKEN value you provide comes from a trusted account; if you prefer less exposure, rely on the anonymous-token flow but be aware it issues short-term credits. (3) Ask the skill author to clarify the metadata mismatch (SKILL.md lists ~/.config/nemovideo/ while registry metadata lists no config paths) and explain exactly what 'auto-detect X-Skill-Platform from install path' entails (it may require reading agent/install metadata). (4) Review the service's terms/privacy and consider using throwaway tokens for trialing the skill.

Getting Started

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

Try saying:

• "generate my images or prompts"
• "export 1080p MP4"
• "generate a 10-second cinematic video from"

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

• Generate a UUID as client identifier
• POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
• The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

Video Leonardo AI — Generate Videos from Images

This tool takes your images or 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 product photo or text description and want to generate a 10-second cinematic video from this image of a forest at sunset — the backend processes it in about 1-3 minutes and hands you a 1080p MP4.

Tip: shorter, specific prompts tend to produce more consistent motion results.

Matching Input to Actions

User prompts referencing video leonardo ai, 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	video-leonardo-ai
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-detect: clawhub / cursor / unknown from install path

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

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 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 10-second cinematic video from this image of a forest at sunset" → 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 cinematic video from this image of a forest at sunset" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across social platforms.