Image To Video No Login

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 requirements and instructions are generally consistent with a cloud-based image→video service, but there are small metadata inconsistencies and an unknown third‑party backend that reduce confidence — review before sending sensitive images or credentials.

Purpose & Capability

The skill claims to convert images to video and its runtime instructions call a video-rendering API, upload endpoints, and export flows — these match the stated purpose. Asking for a single service token (NEMO_TOKEN) is expected. Minor incoherence: the registry metadata listed no required config paths, but the SKILL.md frontmatter references a config path (~/.config/nemovideo/); this is likely benign but inconsistent.

Instruction Scope

Instructions stay within the video-rendering domain: session creation, SSE streaming, uploads, polling render status, and exporting. The skill also asks the agent to detect install path to set an X-Skill-Platform header (reading local install paths like ~/.clawhub/ or ~/.cursor/skills/) and to read the SKILL.md frontmatter at runtime — these require the agent to inspect local paths/files. That behavior is explainable (attribution) but worth noting since it touches the filesystem beyond purely reading user-uploaded images.

Install Mechanism

There is no install spec and no code files — instruction-only skills are lowest risk from an install perspective. Nothing is downloaded or written to disk by an installer in the provided spec.

Credentials

The skill declares a single primary credential (NEMO_TOKEN), which fits a remote service integration. The skill will also attempt to obtain an anonymous token automatically if NEMO_TOKEN is not present — a plausible 'no login' design. The frontmatter also lists a config path (~/.config/nemovideo/) which was not listed in the registry metadata; asking to access that config path could be reasonable but should be justified. No unrelated credentials are requested.

Persistence & Privilege

always:false (default) and no install steps are present. The skill instructs storing session_id for subsequent API calls (normal ephemeral state). It does not request persistent system-wide privileges or change other skills' configs.

Assessment

This skill appears to be a straightforward cloud-based image→video converter and asks only for a service token (which it can also obtain anonymously). Before installing or using it: 1) Be aware your images will be uploaded to a third‑party domain (mega-api-prod.nemovideo.ai). Do not send private or sensitive images unless you trust that service and have reviewed its privacy terms. 2) The skill will read its own SKILL.md and try to detect install paths (to set an attribution header); if you prefer not to expose local install layout, avoid using it or run in a sandbox. 3) Note the minor metadata mismatch about a config path — this is probably harmless but suggests the authoring was not fully consistent. 4) If you need higher assurance, ask the author or vendor for a homepage/privacy policy, the exact domain ownership, and whether uploads are retained; also check network activity during a test run. If any of those are missing or the backend is untrusted, treat it as untrusted software and avoid sending sensitive data.

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 photos into a 15-second"

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 No Login — Convert Images Into Video Instantly

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 three product photos in JPG format, ask for turn these photos into a 15-second video with transitions, and about 20-40 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — fewer images per batch means faster processing and quicker downloads.

Matching Input to Actions

User prompts referencing image to video no login, 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: image-to-video-no-login
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else 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.

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)

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 → "turn these photos into a 15-second video with transitions" → 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 "turn these photos into a 15-second video with transitions" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across all platforms.