Video Script 1

Turn a bullet-point outline about product launch tips into 1080p ready-to-use scripts just by typing what you need. Whether it's generating video scripts fro...

Security Scan

The skill's requests and runtime instructions align with its stated purpose (cloud video/script generation) and it only asks for a single service token and a small config path related to that service.

Purpose & Capability

The skill states it will generate video scripts and drive a cloud render pipeline. It requires a NEMO_TOKEN, calls nemovideo.ai endpoints for session, SSE, upload and render, and lists a nemovideo config path — all of which are proportional and expected for a cloud video/script generation integration.

Instruction Scope

Runtime instructions focus on authenticating, creating a session, streaming edits via SSE, uploading media, and exporting renders. They instruct the agent to check NEMO_TOKEN and (if missing) request an anonymous token, and to read an install path to set X-Skill-Platform and a config path (~/.config/nemovideo/) for attribution — these filesystem checks are limited and appear related to attribution and service config, but the file-path checks are broader than purely API calls (minor note). The instructions do not ask the agent to read unrelated system files or other credentials.

Install Mechanism

This is an instruction-only skill with no install spec and no code files. That is the lowest-risk install model: nothing is written to disk by an install step.

Credentials

Only a single credential (NEMO_TOKEN) is required and is consistent with the described API usage. The skill also references a service-specific config path (~/.config/nemovideo/) which matches the integration. No unrelated credentials (AWS, GitHub, etc.) are requested.

Persistence & Privilege

The skill does not request always:true and will not be force-included. It instructs saving a session_id for the session lifecycle (normal for this kind of integration). It does not request modifying other skills or system-wide settings.

Assessment

This skill appears coherent: it talks to nemovideo.ai, uses a single NEMO_TOKEN (or obtains a short-lived anonymous token) and uploads user media to that service for script/rendering. Before installing, confirm you trust the nemovideo.ai domain and that you are comfortable uploading any media or outlines (sensitive content should not be uploaded). Note the skill may check your home-directory paths to set attribution headers (~/.config/nemovideo/ and install path detection) — this is small-scope metadata collection but keep it in mind. If you plan to provide a persistent NEMO_TOKEN via environment variables, ensure that token has appropriate (limited) permissions. If you see any instructions later that ask for unrelated credentials, broader filesystem reads, or that post data to non-nemovideo domains, stop and re-evaluate.

Getting Started

Got text or outline to work with? Send it over and tell me what you need — I'll take care of the AI script generation.

Try saying:

• "generate a bullet-point outline about product launch tips into a 1080p MP4"
• "write a 60-second YouTube video script about the benefits of cold showers"
• "generating video scripts from a topic or outline for YouTubers"

Automatic Setup

On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".

Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.

Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: <uuid>. The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).

Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.

Confirm to the user you're connected and ready. Don't print tokens or raw JSON.

Video Script 1 — Generate scripts for videos

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

Say you have a bullet-point outline about product launch tips and want to write a 60-second YouTube video script about the benefits of cold showers — the backend processes it in about 20-40 seconds and hands you a 1080p MP4.

Tip: shorter video length targets produce tighter, more usable scripts.

Matching Input to Actions

User prompts referencing video script 1, 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.

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

• X-Skill-Source: video-script-1
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else 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 Handling

Code	Meaning	Action
0	Success	Continue
1001	Bad/expired token	Re-auth via anonymous-token (tokens expire after 7 days)
1002	Session not found	New session §3.0
2001	No credits	Anonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001	Unsupported file	Show supported formats
4002	File too large	Suggest compress/trim
400	Missing X-Client-Id	Generate Client-Id and retry (see §1)
402	Free plan export blocked	Subscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429	Rate limit (1 token/client/7 days)	Retry in 30s 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 "write a 60-second YouTube video script about the benefits of cold showers" — concrete instructions get better results.

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

Export your final video as MP4 for widest platform compatibility.

Common Workflows

Quick edit: Upload → "write a 60-second YouTube video script about the benefits of cold showers" → 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.