Generator Generator Simple

Skip the learning curve of professional editing software. Describe what you want — generate a simple 30-second video from this text prompt — and get generate...

Security Scan

The skill's stated purpose (generate short videos via a cloud backend) is plausible, but there are inconsistencies and a few behaviors that deserve caution before installing.

Purpose & Capability

The skill claims to perform cloud video generation and only requests a single credential (NEMO_TOKEN), which matches the purpose. However the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata lists no required config paths — an internal inconsistency about what local config it expects.

Instruction Scope

Instructions are explicit about creating a session, uploading media, streaming SSE for generation, and exporting results to a download URL on mega-api-prod.nemovideo.ai. It also instructs the agent to automatically obtain an anonymous token if NEMO_TOKEN is missing (POST to /api/auth/anonymous-token). Automatically acquiring and using credentials on first use is plausible but broad — it means the skill will call an external auth endpoint and then use that token to upload user media. The instructions do not direct the agent to read unrelated files or unrelated env vars, but they do describe determining an 'install path' to set an X-Skill-Platform header (this implies checking agent install paths), which is peripheral to core generation functionality.

Install Mechanism

No install spec or code files are present; this is instruction-only, so nothing will be written to disk by an installer. That minimizes install-time risk.

Credentials

The primaryEnv is NEMO_TOKEN which is appropriate for a cloud video service. But the SKILL.md frontmatter declares a configPaths entry (~/.config/nemovideo/) while the registry metadata shows no required config paths — this mismatch is unexplained. Also the skill will automatically request and use an anonymous token if none is present, which could create credentials without an explicit user action and lead to uploads under that anonymous account. The headers and attribution requirements (X-Skill-Source / Version / Platform) are unusual but not inherently malicious; they do add identifiers that are sent with every request.

Persistence & Privilege

The skill is not always-enabled and does not request elevated platform privileges. Autonomous invocation is allowed (default) but not combined with other high-risk factors here. The skill does interact with a remote service and may create session tokens, but it does not declare any ability to modify other skills or system-wide settings.

What to consider before installing

This skill will upload your media and prompts to a remote service (mega-api-prod.nemovideo.ai) and needs a NEMO_TOKEN. If you don't provide one, it will automatically request an anonymous token and use that account to run jobs. Before installing, confirm: 1) the service domain is trustworthy and you accept uploading potentially sensitive media there; 2) where and whether the anonymous token or any credentials are stored (are they persisted to disk under ~/.config/nemovideo/?); 3) the privacy/retention policy for uploaded videos. Also ask the publisher to fix the metadata inconsistency about required config paths and to document exactly what local paths (if any) will be read or written and how long anonymous tokens/credits persist. If you need stronger assurance, request the skill source or a privacy policy link.

Getting Started

Share your text prompts and I'll get started on AI video generation. Or just tell me what you're thinking.

Try saying:

• "generate my text prompts"
• "export 1080p MP4"
• "generate a simple 30-second video from"

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.

Generator Generator Simple — Generate Videos From Simple Inputs

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

Say you have a short text description of a scene or concept and want to generate a simple 30-second video from this text prompt — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: shorter and clearer prompts produce more accurate results.

Matching Input to Actions

User prompts referencing generator generator simple, 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 generator-generator-simple, 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

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 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 "generate a simple 30-second video from this text prompt" — concrete instructions get better results.

Max file size is 200MB. Stick to MP4, MOV, WebM, GIF for the smoothest experience.

Export as MP4 for widest compatibility.

Common Workflows

Quick edit: Upload → "generate a simple 30-second video from this text prompt" → 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.