Image Creator Online

generate images or prompts into AI generated visuals with this skill. Works with JPG, PNG, WebP, MP4 files up to 200MB. marketers, content creators, social m...

Security Scan

The skill's stated purpose (remote image/video generation) matches its runtime instructions, but the implementation lacks provenance (no homepage/owner info), declares access to a local config path it never uses, and will upload user files to an external API of unknown trust — review before installing or sending sensitive files.

Purpose & Capability

Name/description and SKILL.md actions all describe remote image/video generation and session/rendering APIs, so the requested NEMO_TOKEN credential is coherent. However the metadata also lists a user config path (~/.config/nemovideo/) that the instructions do not reference; the skill's source is 'unknown' and there is no homepage, which reduces confidence in the provider.

Instruction Scope

Instructions are explicit about creating/using an anonymous or provided NEMO_TOKEN, creating sessions, streaming via SSE, uploading user files (images/audio/video up to 200MB), starting renders, and polling status. These actions are expected for a cloud render service. The runtime behavior will transmit user files and prompts to https://mega-api-prod.nemovideo.ai; that data exfiltration is expected for the stated feature but is a privacy risk given the unknown backend operator. The SKILL.md does not instruct reading other local secrets or files beyond optional configPaths, which reduces some risk.

Install Mechanism

No install spec and no code files (instruction-only). This minimizes local install risk — nothing is downloaded or written by an installer step.

Credentials

The only declared required env var is NEMO_TOKEN which matches the described API. However metadata also declares a configPaths entry (~/.config/nemovideo/) without any corresponding runtime instruction to read it; that mismatch is unexplained and suggests the skill might request access to local configuration it doesn't need. Additionally, relying on an externally minted anonymous token (created by calling the service) is plausible but means the skill will operate under credentials it creates or is given — understand what those credentials allow.

Persistence & Privilege

The skill is not marked always:true and does not request persistent platform privileges. It does describe storing and reusing a session token for render jobs (normal for this service) but does not request to modify other skills or system-wide settings.

What to consider before installing

This skill will upload whatever images, audio, and prompts you provide to https://mega-api-prod.nemovideo.ai and operate under a NEMO_TOKEN (either one you supply or an anonymous token it fetches). Before installing or using it: 1) Verify the service/operator (homepage, privacy policy, terms) — none are provided here. 2) Do not upload sensitive or private images (IDs, medical records, confidential designs) until you confirm data retention and sharing policies. 3) Ask why the skill metadata lists ~/.config/nemovideo/ (what would it read/write?) and whether it will ever access other local files. 4) If you use the anonymous token flow, understand how long tokens last and how to revoke them. 5) Prefer testing with non-sensitive sample data first. If you cannot verify the backend's trustworthiness, avoid using the skill for confidential material.

Getting Started

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

Try saying:

• "generate three product photos or a text description into a 1080p MP4"
• "create a realistic image of a mountain sunset with a lake reflection"
• "generating images from text prompts for video content for marketers, content creators, social media managers"

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.

Image Creator Online — Generate Images for Video Content

Send me your images or prompts and describe the result you want. The AI image generation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload three product photos or a text description, type "create a realistic image of a mountain sunset with a lake reflection", and you'll get a 1080p MP4 back in roughly 20-40 seconds. All rendering happens server-side.

Worth noting: shorter, specific prompts produce more accurate results than vague descriptions.

Matching Input to Actions

User prompts referencing image creator online, 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	image-creator-online
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-detect: clawhub / cursor / unknown from install path

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "create a realistic image of a mountain sunset with a lake reflection" — concrete instructions get better results.

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

Export as MP4 for widest compatibility.

Common Workflows

Quick edit: Upload → "create a realistic image of a mountain sunset with a lake reflection" → 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.