Jpg To Video

turn still images into animated slideshow video with this skill. Works with JPG, PNG, WEBP, HEIC files up to 200MB. marketers, social media creators use it f...

Security Scan

The skill's requests and runtime instructions match its stated purpose (upload images, call a cloud render API, and return videos); nothing in the manifest is disproportionate or clearly unrelated to image→video conversion.

Purpose & Capability

Name/description (convert still images to videos) aligns with required credential (NEMO_TOKEN) and the SKILL.md which describes uploading images, creating sessions, streaming edits, and requesting exports from a cloud render backend. Requiring an API token for a third‑party rendering service is expected.

Instruction Scope

SKILL.md confines activity to contacting the nemovideo API, uploading user-supplied files, handling SSE streams, polling job state, and returning download URLs. It does instruct generating or storing an anonymous token and session_id; it does not instruct reading arbitrary local files or unrelated credentials. The doc also says to keep tokens hidden from the user but to store them — where and how they are stored is not specified.

Install Mechanism

Instruction-only skill with no install spec or code files. No binaries or third-party installs are requested, so there is no installation risk.

Credentials

Only NEMO_TOKEN is declared as required (primary credential), which is proportional to calling a third‑party API. The SKILL.md also auto‑generates an anonymous token if NEMO_TOKEN is not present. Metadata lists a config path (~/.config/nemovideo/) — the README does not explicitly say it will read/write that path, but the presence of a config path implies the skill may persist tokens/session data locally; the skill does not request other unrelated secrets.

Persistence & Privilege

always is false and the skill is user‑invocable. Autonomous invocation (model calls) is allowed by default but not combined with other red flags. The skill intends to store a token/session_id (normal for API clients) but does not request system‑wide privileges or modify other skills' configs.

Assessment

This skill appears to do what it says: upload images to a cloud rendering service and return an MP4. Before installing, consider: (1) it requires an API token (NEMO_TOKEN) but will create an anonymous token for you if none is supplied — that token and session_id will be stored (metadata hints at ~/.config/nemovideo/), so verify where/if credentials are saved and how they are protected; (2) your images and any audio you upload are sent to https://mega-api-prod.nemovideo.ai — review the service's privacy policy and retention rules before uploading sensitive content; (3) if you have a paid account, prefer providing your own NEMO_TOKEN rather than using anonymous tokens; (4) confirm the backend domain is legitimate for your use case. If you need higher assurance, ask the skill author where tokens are stored and whether uploads are deleted after processing.

Getting Started

Share your still images and I'll get started on AI video creation. Or just tell me what you're thinking.

Try saying:

• "turn my still images"
• "export 1080p MP4"
• "turn these photos into a 30-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.

JPG to Video — Convert Photos Into Shareable Videos

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

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

Tip: fewer images with longer durations per image tend to look more polished than rapid-fire slideshows.

Matching Input to Actions

User prompts referencing jpg to video, 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.

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

All requests must include: Authorization: Bearer <NEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 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 → "turn these photos into a 30-second slideshow video with 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn these photos into a 30-second 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 social platforms.