Ai Animation Logo

Turn a PNG logo on transparent background into 1080p animated logo video just by typing what you need. Whether it's creating animated logo intros for videos...

Security Scan

The skill's requirements and runtime instructions are coherent with a cloud-based logo animation service, but there are small mismatches (frontmatter vs. registry metadata) and it will make network calls and read a couple of local paths — review data/credential decisions before installing.

Purpose & Capability

Name/description (animate PNG logos into 1080p video) match the runtime instructions: upload a logo, create a session, send render requests, poll status, and return a download URL. Requesting a NEMO_TOKEN credential to authorize API calls is consistent with a hosted rendering service.

Instruction Scope

Instructions include all steps needed to talk to the remote API (anonymous-token fallback, session creation, SSE handling, uploads, rendering). They also instruct the agent to read the skill's YAML frontmatter and detect install path (e.g., ~/.clawhub/, ~/.cursor/skills/) to set X-Skill-Platform — this requires reading a few paths in the user's home directory. That file-system access is limited but not declared in registry metadata (see environment_proportionality).

Install Mechanism

Instruction-only skill with no install spec and no code files — lowest installer risk. Nothing is downloaded or written to disk by an install step.

Credentials

The skill declares a single primary environment variable (NEMO_TOKEN), which matches the API-based workflow. However, the SKILL.md frontmatter references a config path (~/.config/nemovideo/) and instructs detecting install paths to set X-Skill-Platform; the registry metadata provided with the submission listed no required config paths. This mismatch should be clarified. The agent will contact an external domain (mega-api-prod.nemovideo.ai) and may exchange uploaded user files and generated tokens with that service.

Persistence & Privilege

always is false and the skill does not request elevated or persistent system-wide privileges. It does not modify other skills or require permanent presence beyond normal runtime invocation. Autonomous invocation is permitted but is the platform default.

Assessment

This skill appears to be what it says: a thin instruction layer that sends your logo and prompts to a remote rendering API. Before installing or invoking it: (1) Confirm you trust https://mega-api-prod.nemovideo.ai and are comfortable that uploaded media and prompts will be transmitted to that service. (2) Consider creating a limited or anonymous NEMO_TOKEN if possible — the skill will also attempt to mint an anonymous token if none is present. (3) Note the SKILL.md asks the agent to read the skill frontmatter and detect install paths (e.g., ~/.clawhub/, ~/.cursor/skills/) and may look at ~/.config/nemovideo/ — if you are uncomfortable with that, ask the publisher to remove or document those steps. (4) The registry metadata and the skill frontmatter disagree about required config paths; request clarification from the publisher. If you rely on sensitive environment credentials elsewhere, avoid supplying them to this skill unless you have verified the service's privacy/retention and billing policies.

Getting Started

Share your logo image or text and I'll get started on AI logo animation. Or just tell me what you're thinking.

Try saying:

• "animate my logo image or text"
• "export 1080p MP4"
• "animate my logo with a smooth"

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 Animation Logo — Animate Logos for Video Intros

Send me your logo image or text and describe the result you want. The AI logo animation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a PNG logo on transparent background, type "animate my logo with a smooth reveal effect for video intros", and you'll get a 1080p MP4 back in roughly 20-40 seconds. All rendering happens server-side.

Worth noting: transparent PNG logos produce the cleanest animation with no background artifacts.

Matching Input to Actions

User prompts referencing ai animation logo, 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.

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

• X-Skill-Source: ai-animation-logo
• 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.

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

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.

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)

Common Workflows

Quick edit: Upload → "animate my logo with a smooth reveal effect for video intros" → Download MP4. Takes 20-40 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "animate my logo with a smooth reveal effect for video intros" — concrete instructions get better results.

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

Export as MP4 with H.264 codec for widest compatibility across platforms.