Ai Video Generator Free Leonardo

generate text prompts or images into AI generated videos with this skill. Works with JPG, PNG, MP4, WebM files up to 200MB. content creators use it for gener...

Security Scan

The skill largely behaves like a cloud video-generation connector, but there are several small inconsistencies (branding vs backend, metadata vs declared requirements, and instructions that imply filesystem probing and broad uploads) that warrant caution before installing or providing real data/credentials.

Purpose & Capability

The skill's stated purpose (AI video generation) matches the API endpoints and flows in SKILL.md (session creation, upload, render). However the name mentions 'Leonardo' while every runtime endpoint and token name is for 'nemovideo.ai' (branding mismatch) — this could be marketing or baiting and should be verified with the publisher. Metadata in the frontmatter also claims a config path (~/.config/nemovideo/) even though the registry summary lists no required config paths (inconsistency).

Instruction Scope

The instructions direct the agent to obtain or use a NEMO_TOKEN and to perform network calls (session, SSE, upload, render polling) to mega-api-prod.nemovideo.ai — all expected for a cloud video service. Concerns: (1) the skill asks the agent to detect install path (~/.clawhub, ~/.cursor/skills/) to populate an attribution header (this requires probing the agent filesystem/environment), (2) upload examples include multipart form with files=@/path which implies reading local filesystem paths if the agent runtime supports it, and (3) the SKILL.md recommends reading the file’s YAML frontmatter at runtime to set headers. These actions expand the agent's data access surface beyond just handling user-uploaded attachments.

Install Mechanism

No install steps or downloaded code are present (instruction-only). This is the lowest-risk install mechanism — nothing is written or executed on disk by the skill package itself.

Credentials

The skill requests a single token (NEMO_TOKEN) which is proportional for an API-backed service. It also provides an anonymous-token fallback flow. Minor inconsistency: frontmatter metadata lists a config path (~/.config/nemovideo/) that wasn't listed by the registry summary; that suggests the skill expects to read local config files in addition to/or instead of an env var in some hosts.

Persistence & Privilege

The skill is not marked always:true and does not request persistent installation or modify other skills. It can be invoked autonomously (platform default), which increases reach but is normal for skills; no additional privilege requests were found.

What to consider before installing

This skill looks like a straightforward cloud video-generation connector, but take precautions before installing or using it with sensitive content or credentials: 1) Verify the publisher and the service domain (nemovideo.ai) — the skill name referencing 'Leonardo' doesn't match the backend and may be misleading. 2) Do not put any sensitive or cross-account credentials in NEMO_TOKEN; create and use a dedicated, limited token if you want to test. 3) Avoid uploading private/proprietary files until you confirm the service's privacy/retention policy (no homepage or docs were provided). 4) Be aware the instructions ask the agent to probe install paths and read frontmatter for headers — this could cause accidental exposure of local config; run in a sandbox or deny filesystem access where possible. 5) If you decide to use it, test first with non-sensitive, throwaway media and monitor outbound network requests to mega-api-prod.nemovideo.ai. If you can, ask the publisher for official documentation, a homepage, and confirmation of the branding/backend relationship before granting any privileges.

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 from this"

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.

AI Video Generator Free Leonardo — Generate Videos from Text or Images

Drop your text prompts or images in the chat and tell me what you need. I'll handle the AI video generation on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a product photo with a short description, ask for generate a 15-second video from this image and text prompt, and about 1-2 minutes later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter prompts with clear subjects produce more consistent results.

Matching Input to Actions

User prompts referencing ai video generator free leonardo, 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.

Skill attribution — read from this file's YAML frontmatter at runtime:

• X-Skill-Source: ai-video-generator-free-leonardo
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)

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

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.

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.

Translating GUI Instructions

The backend responds as if there's a visual interface. Map its instructions to API calls:

• "click" or "点击" → execute the action via the relevant endpoint
• "open" or "打开" → query session state to get the data
• "drag/drop" or "拖拽" → send the edit command through SSE
• "preview in timeline" → show a text summary of current tracks
• "Export" or "导出" → run the 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)

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

Common Workflows

Quick edit: Upload → "generate a 15-second video from this image and text prompt" → 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 from this image and text prompt" — concrete instructions get better results.

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

Export as MP4 for widest compatibility.