Ai Animation Free

Get animated video clips ready to post, without touching a single slider. Upload your images or text (PNG, JPG, MP4, GIF, up to 200MB), say something like "a...

Security Scan

The skill's networked animation workflow is plausible, but there are inconsistencies about required config access and token handling that you should understand before installing or providing credentials.

Purpose & Capability

The declared need for a NEMO_TOKEN and the described API endpoints align with a cloud animation service. However the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata at the top of the package said no config paths are required — this mismatch is unexplained.

Instruction Scope

Instructions are largely scoped to uploading files and interacting with the remote nemovideo API (session creation, SSE, render polling). They tell the agent to read NEMO_TOKEN and to auto-acquire an anonymous token if none exists. The agent is also asked to ‘auto-detect’ an install path for X-Skill-Platform, which implies reading local install/agent path information — a small scope creep that should be explicit.

Install Mechanism

This is an instruction-only skill with no install spec or code to write to disk, which is the lowest-risk install model.

Credentials

Requesting a single service token (NEMO_TOKEN) is proportional for a hosted renderer, but the package is inconsistent: the registry declares NEMO_TOKEN as required while the runtime instructions will also obtain an anonymous token if none is provided. Additionally, the SKILL.md claims access to a user config path (~/.config/nemovideo/) that is not listed in the registry metadata — that suggests the skill may read or write files in the user's home config directory, which should be justified.

Persistence & Privilege

The skill keeps a session_id and token for the session and may store or reuse them, but it does not declare 'always: true' or other elevated privileges. You should confirm where (if anywhere) tokens or session state are persisted (memory only vs. config files).

What to consider before installing

This skill appears to do what it says (upload images, call a cloud API, return MP4s) but has inconsistent metadata about config access and token handling. Before installing or enabling it: 1) verify the domain (mega-api-prod.nemovideo.ai) and the service’s legitimacy; 2) decide whether you want to provide a permanent NEMO_TOKEN as an env var or let the skill obtain an anonymous token (which grants temporary access); 3) ask the author whether the skill will read or write ~/.config/nemovideo/ (and where tokens/session IDs are stored); 4) avoid uploading sensitive or private images unless you trust the backend and its privacy policy; and 5) if you allow autonomous invocation, be aware the agent can call the external API (start jobs, upload files) without further prompts. If the author can clarify the config-path discrepancy and token storage location, the remaining concerns would be reduced.

Getting Started

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

Try saying:

• "convert a series of five character illustration frames into a 1080p MP4"
• "animate these still images into a smooth motion sequence"
• "turning static images into animated videos for content creators"

Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:

• Generate a UUID as client identifier
• POST https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
• Extract data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

AI Animation Free — Convert Images Into Animated Videos

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

Here's a typical use: you send a a series of five character illustration frames, ask for animate these still images into a smooth motion sequence, 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 — simpler backgrounds animate more cleanly and process faster.

Matching Input to Actions

User prompts referencing ai animation 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.

Three attribution headers are required on every request and must match this file's frontmatter:

Header	Value
X-Skill-Source	ai-animation-free
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-detect: clawhub / cursor / unknown from install path

Every API call needs Authorization: Bearer <NEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

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 → "animate these still images into a smooth motion sequence" → 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 "animate these still images into a smooth motion sequence" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across social platforms.