Image To Video Leaderboard Ai

v1.0.0

Turn a single product photo or illustration into 1080p animated video clips just by typing what you need. Whether it's converting still images into videos us...

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for dsewell-583h0/image-to-video-leaderboard-ai.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Image To Video Leaderboard Ai" (dsewell-583h0/image-to-video-leaderboard-ai) from ClawHub.
Skill page: https://clawhub.ai/dsewell-583h0/image-to-video-leaderboard-ai
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Required env vars: NEMO_TOKEN
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install image-to-video-leaderboard-ai

ClawHub CLI

Package manager switcher

npx clawhub@latest install image-to-video-leaderboard-ai
Security Scan
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OpenClawOpenClaw
Benign
medium confidence
Purpose & Capability
Name/description align with the actions in SKILL.md: image upload, session creation, job submission, and download. The declared primary environment variable (NEMO_TOKEN) is appropriate for an API-backed video render service. Note: the YAML frontmatter includes a required config path (~/.config/nemovideo/) but the registry metadata earlier reported no required config paths — this is an internal inconsistency to be aware of.
Instruction Scope
Runtime instructions are explicit and limited to: check for NEMO_TOKEN, optionally obtain an anonymous token from the service, create a session, upload files (by file path or URL), use SSE or polling for generation, and retrieve output URLs. These steps necessarily read user-supplied image files (or URLs) and detect certain install paths for header metadata. The instructions also direct the agent to store session_id (and implicitly handle/retain tokens) and to avoid echoing raw tokens to the user. This scope is coherent for the feature, but it involves sending potentially sensitive images to an external API and persisting short-lived tokens/session IDs.
Install Mechanism
No install specification or third-party packages — instruction-only. Nothing is written to disk by an automated installer according to the manifest, which minimizes install-time risk.
Credentials
Only one credential (NEMO_TOKEN) is required; that is proportional to the described cloud API usage. The skill also documents how to obtain an anonymous token if none is present. The earlier-noted mismatch between the frontmatter's configPaths and the registry's 'none' should be clarified (the skill declares ~/.config/nemovideo/ in its YAML).
Persistence & Privilege
always is false and the skill does not request elevated or system-wide privileges. It does instruct the agent to store session_id and manage short-lived tokens for continued API calls — normal for this kind of integration. There is no instruction to modify other skills or global agent settings.
Assessment
This skill appears to do what it says: it will upload images to an external service (mega-api-prod.nemovideo.ai), generate short-lived session tokens (or use NEMO_TOKEN if provided), and return download URLs. Before installing: (1) Confirm you trust the external service — there is no homepage or provenance in the registry entry. (2) Do not upload sensitive or private images unless you accept external processing and storage. (3) Prefer supplying your own NEMO_TOKEN from a trusted account if you want control over credentials and revocation. (4) Ask where the skill stores session IDs/tokens (in-memory vs disk) and how long uploaded media is retained. (5) Clarify the YAML frontmatter vs registry discrepancy for config paths. If you are comfortable with these tradeoffs, the skill is internally coherent for its advertised purpose.

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

🏆 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk97cs4kpsgx57xwd5ka5w2m3fx85harq
57downloads
0stars
1versions
Updated 3d ago
v1.0.0
MIT-0

Getting Started

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

Try saying:

  • "convert my images"
  • "export 1080p MP4"
  • "compare top AI models and generate"

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.

Image to Video Leaderboard AI — Compare AI Models, Generate Videos

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

Here's a typical use: you send a a single product photo or illustration, ask for compare top AI models and generate a video from my image using the best-ranked one, and about 30-90 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — higher-ranked models on the leaderboard tend to produce smoother motion and fewer artifacts.

Matching Input to Actions

User prompts referencing image to video leaderboard ai, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

User says...ActionSkip 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.

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

Headers are derived from this file's YAML frontmatter. X-Skill-Source is image-to-video-leaderboard-ai, 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 Handling

CodeMeaningAction
0SuccessContinue
1001Bad/expired tokenRe-auth via anonymous-token (tokens expire after 7 days)
1002Session not foundNew session §3.0
2001No creditsAnonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001Unsupported fileShow supported formats
4002File too largeSuggest compress/trim
400Missing X-Client-IdGenerate Client-Id and retry (see §1)
402Free plan export blockedSubscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429Rate limit (1 token/client/7 days)Retry in 30s once

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend saysYou 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

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.

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "compare top AI models and generate a video from my image using the best-ranked one" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across social and web platforms.

Common Workflows

Quick edit: Upload → "compare top AI models and generate a video from my image using the best-ranked one" → Download MP4. Takes 30-90 seconds 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.

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