To Generation Generator

Turn a short text description of a scene or topic into 1080p generated video clips just by typing what you need. Whether it's generating videos from text pro...

Security Scan

The skill's declared purpose (text→video generation) matches its runtime instructions and requested credential (NEMO_TOKEN); small metadata and workflow inconsistencies are worth noting before use.

Purpose & Capability

The skill claims to generate videos from text and all required actions (session creation, upload, render/export) and the single credential NEMO_TOKEN are coherent with that purpose.

Instruction Scope

SKILL.md instructs the agent to call nemo backend APIs, create sessions, upload files, stream SSE messages and poll render status — all expected. It also specifies auto-acquiring an anonymous token via a POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token when NEMO_TOKEN is missing. The instructions ask the agent to 'auto-detect' platform from the install path, which implies reading install/config path information (not fully declared). No instructions ask for unrelated system files or unrelated credentials.

Install Mechanism

This is an instruction-only skill with no install spec or code files, so nothing is written to disk by an installer. That's the lowest-risk install footprint.

Credentials

The only required environment credential is NEMO_TOKEN, which is appropriate for a cloud video service. Minor inconsistency: the registry metadata earlier listed no required config paths, but the SKILL.md frontmatter includes a config path (~/.config/nemovideo/). Also, the SKILL.md provides a fallback to obtain an anonymous token if NEMO_TOKEN is absent, which is sensible but means the platform's 'required env var' designation may be stricter than the skill actually needs.

Persistence & Privilege

The skill is not force-included (always:false) and does not request system-wide persistent privileges. It does require network calls to the backend, but that is expected for its function.

Assessment

This skill appears coherent for text→video generation, but check the following before installing: 1) Verify the backend domain (mega-api-prod.nemovideo.ai) is trustworthy for your use — the skill will call it and can obtain an anonymous token if you don't supply one. 2) Decide whether you want to set a NEMO_TOKEN in your environment or rely on the anonymous-token flow (anonymous tokens are short-lived and provide limited credits). 3) Note the SKILL.md references a config path (~/.config/nemovideo/) and auto-detecting install path for X-Skill-Platform; confirm whether the agent will read those filesystem locations and whether you’re comfortable with that. 4) If you need stronger assurance, request the skill's source or an official homepage and verify ownership of the nemo domain and API behavior. Providing network access and a service token is required for this skill to function; avoid supplying long-lived credentials unless you trust the service.

Getting Started

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

Try saying:

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

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.

To Generation Generator — Generate Videos From Text

This tool takes your text or 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 topic and want to generate a 30-second video from this script about climate change — the backend processes it in about 1-3 minutes and hands you a 1080p MP4.

Tip: shorter and more specific prompts tend to produce more accurate video results.

Matching Input to Actions

User prompts referencing to generation generator, 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.

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.

Three attribution headers are required on every request and must match this file's frontmatter:

Header	Value
X-Skill-Source	to-generation-generator
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-detect: clawhub / cursor / unknown from install path

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)

Common Workflows

Quick edit: Upload → "generate a 30-second video from this script about climate change" → Download MP4. Takes 1-3 minutes 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 "generate a 30-second video from this script about climate change" — concrete instructions get better results.

Max file size is 200MB. Stick to TXT, DOCX, PDF, MP4 for the smoothest experience.

Export as MP4 for widest compatibility.