Jpg To Video Maker Free

convert images into slideshow MP4 video with this skill. Works with JPG, PNG, WEBP, HEIC files up to 200MB. social media creators use it for turning photo co...

Security Scan

The skill's functionality (upload images -> remote render -> return MP4) is coherent, but there are mismatches and privacy risks: it will obtain/store an anonymous token and upload your photos to an external API with no identifiable publisher or homepage, and the manifest/frontmatter disagree about local config usage.

Purpose & Capability

The declared purpose (convert images to MP4 via a cloud renderer) aligns with the only required credential (NEMO_TOKEN) and the API endpoints in SKILL.md. However the skill has no listed homepage or source, which reduces transparency and makes it harder to verify the backend's trustworthiness.

Instruction Scope

Instructions tell the agent to obtain an anonymous token automatically, create and persist a session_id, and upload user files to https://mega-api-prod.nemovideo.ai. This necessarily transmits user images and metadata to a third party (privacy risk). The runtime also instructs the agent to inspect local install paths and a config directory (~/.config/nemovideo/) to set attribution headers, which involves reading the user filesystem beyond just consuming user-supplied image files.

Install Mechanism

Instruction-only skill with no install script or downloaded code. This minimizes on-disk persistence and arbitrary code execution risk.

Credentials

Only NEMO_TOKEN is required and fits the described backend usage. However the frontmatter declares a config path (~/.config/nemovideo/) while registry metadata listed no required config paths — that's an inconsistency. The skill's instructions also imply storing tokens/session IDs (potentially to disk), so confirm what gets written and where before installing.

Persistence & Privilege

always:false and no explicit privileged flags. Still, the runtime asks to 'store the returned session_id for all subsequent requests' and references a config directory; that suggests the skill may persist tokens/session info locally. There is no 'always:true' or other elevated privilege requested.

What to consider before installing

This skill appears to do what it says (remote rendering of photos to MP4), but it relies on an external API hosted at an unknown domain and will upload your images there. Before installing, consider: (1) Do you trust the backend operator? There is no homepage or source repository. (2) The skill can auto-generate and store an anonymous token and session ID — find out if and where those are written (frontmatter mentions ~/.config/nemovideo/). (3) Avoid uploading private or sensitive photos until you verify the service's privacy policy and storage practices. (4) If you require more assurance, ask the publisher for source code or an official homepage, or test with non-sensitive images and monitor what files are created under your home directory.

Getting Started

Send me your images and I'll handle the video creation. Or just describe what you're after.

Try saying:

• "convert five vacation JPG photos into a 1080p MP4"
• "turn these photos into a slideshow video with transitions"
• "turning photo collections into shareable videos for social media creators"

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.

JPG to Video Maker Free — Convert Photos into MP4 Videos

Send me your images and describe the result you want. The video creation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload five vacation JPG photos, type "turn these photos into a slideshow video with transitions", and you'll get a 1080p MP4 back in roughly 20-40 seconds. All rendering happens server-side.

Worth noting: fewer images with longer durations per photo look more professional than rapid slideshows.

Matching Input to Actions

User prompts referencing jpg to video maker 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.

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

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

• X-Skill-Source: jpg-to-video-maker-free
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else 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 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

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

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.

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn these photos into a slideshow video with 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 all platforms and devices.

Common Workflows

Quick edit: Upload → "turn these photos into a slideshow 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.