Ai Image To Video Maker

Turn three product photos in JPG format into 1080p animated video clips just by typing what you need. Whether it's converting still images into shareable vid...

Security Scan

The skill's declared purpose (convert images to short videos) matches most of its instructions, but there are minor inconsistencies and some ambiguous behaviors (token handling, filesystem detection) that the user should understand before installing.

Purpose & Capability

Name/description align with the actions in SKILL.md (upload images, request render, download URL). The only required credential is NEMO_TOKEN which is proportionate. However the SKILL.md frontmatter declares a config path (~/.config/nemovideo/) even though registry metadata listed no required config paths — this mismatch is unexplained.

Instruction Scope

Runtime instructions are focused on the declared task: creating sessions, uploading files, SSE for edits, polling render status. They do require network calls to mega-api-prod.nemovideo.ai and uploading user files (expected). Ambiguities: instructions say to detect install path to set an attribution header (this implies reading filesystem/environment), and the docs say the anon token becomes your NEMO_TOKEN but do not specify where/how to persist it — these give the agent discretion to read/write state beyond the minimal API calls.

Install Mechanism

Instruction-only skill with no install steps and no code files. No downloads or executables are requested, which is low risk for installation.

Credentials

Only one environment credential (NEMO_TOKEN) is required and is appropriate for a cloud-rendering API. The SKILL.md offers a way to obtain an anonymous token automatically (POST with a generated UUID) — legitimate but raises questions about where that token will be stored. The presence of a configPaths entry in the skill's frontmatter is inconsistent with the registry's 'no required config paths'.

Persistence & Privilege

always:false (no forced presence) and normal autonomous invocation allowed. The skill does instruct saving session_id from API responses (expected for session management) but does not request system-wide configuration changes. No evidence it modifies other skills or global agent settings.

What to consider before installing

This skill mostly does what it says: it uploads images you provide to a remote render API and returns a download link. Before installing, consider: (1) the skill will make network calls to https://mega-api-prod.nemovideo.ai — only use it if you trust that service; (2) it can upload any files you give it, so don't send sensitive documents or images; (3) it can auto-generate an anonymous token and may store session tokens — ask the developer where tokens/session IDs are saved and how long they're retained; (4) there's a small metadata mismatch (a config path in SKILL.md that isn't listed in registry metadata) and it may try to read your install path to set headers — if you want stricter privacy, insist the agent not probe filesystem paths and prefer to provide your own NEMO_TOKEN rather than letting the skill generate/store one automatically. If you need higher assurance, request the skill author to clarify storage behavior and remove the ambiguous configPath/install-path detection.

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"
• "turn these images into a 15-second"

Automatic Setup

On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".

Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.

Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: <uuid>. The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).

Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.

Confirm to the user you're connected and ready. Don't print tokens or raw JSON.

AI Image to Video Maker — Convert Images into Videos

This tool takes your images and runs AI video creation through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have three product photos in JPG format and want to turn these images into a 15-second video with smooth transitions — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: using high-resolution images produces sharper output video.

Matching Input to Actions

User prompts referencing ai image to video maker, 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.

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

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

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.

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 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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn these images into a 15-second video with smooth transitions" — 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 platforms.

Common Workflows

Quick edit: Upload → "turn these images into a 15-second video with smooth transitions" → Download MP4. Takes 30-60 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.