Sora Ai Video Maker

content creators generate text prompts into AI generated videos using this skill. Accepts MP4, MOV, WebM, GIF up to 500MB, renders on cloud GPUs at 1080p, an...

Security Scan

The skill's requests and runtime instructions are consistent with a cloud-based AI video generation service: it needs a NEMO_TOKEN, uploads media to the provider, and talks to the nemovideo.ai API; there are no surprising credentials or installs.

Purpose & Capability

Name/description, declared credential (NEMO_TOKEN), and the SKILL.md API endpoints all align with a cloud video render service. The skill requires only a service token and performs uploads, SSE, and render requests consistent with the stated goal.

Instruction Scope

Instructions tell the agent to (a) obtain or use NEMO_TOKEN, (b) create sessions, (c) upload user media, (d) stream/poll SSE endpoints and return download URLs. These are appropriate for the stated function. The skill also instructs the agent to read the skill's frontmatter and detect install path to populate attribution headers; that requires reading skill metadata / runtime install path (reasonable but broader than purely 'generate video'). No instructions request unrelated files, system secrets, or arbitrary local data.

Install Mechanism

There is no install spec and no code files — this is an instruction-only skill. That is the lowest-risk install profile (nothing is written to disk by an installer).

Credentials

Only one credential (NEMO_TOKEN) is required and is the primaryEnv; this is proportionate for a cloud API. The skill can also request/generate an anonymous token itself via the provider's anonymous-token endpoint (so it can operate without a pre-set token). One minor inconsistency: the SKILL.md frontmatter includes a configPaths entry (~/.config/nemovideo/) while the registry metadata shown earlier listed no required config paths — the skill may expect to read/write a local config directory for token/session caching, which is plausible but worth verifying.

Persistence & Privilege

always:false and normal model invocation are used (no forced global inclusion). The skill instructs storing session_id and may cache tokens/sessions locally (consistent with services that resume jobs), but it does not request elevated or cross-skill persistence beyond its own config area.

Assessment

This skill appears to do what it says, but before installing: (1) understand that your uploaded media will be sent to https://mega-api-prod.nemovideo.ai for processing — ensure you are comfortable with that external upload and any privacy/billing implications; (2) the skill will use or create a NEMO_TOKEN (it can auto-generate an anonymous token valid 7 days) and may cache session/token data in a local config path (~/.config/nemovideo/) — confirm whether you want tokens stored locally; (3) registry metadata and the SKILL.md disagree about config path requirements — ask the publisher which local paths will be used and for what purpose; (4) if you prefer, provide your own NEMO_TOKEN rather than allowing the skill to auto-generate one; (5) no installers or other credentials are requested, which reduces risk, but always review the provider domain and privacy policy before uploading sensitive content.

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 10-second video of a"

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.

Sora AI Video Maker — Generate Videos From Text Prompts

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 and want to generate a 10-second video of a sunset over the ocean with calm waves — the backend processes it in about 1-3 minutes and hands you a 1080p MP4.

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

Matching Input to Actions

User prompts referencing sora ai video maker, 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: sora-ai-video-maker
• 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

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.

Translating GUI Instructions

The backend responds as if there's a visual interface. Map its instructions to API calls:

• "click" or "点击" → execute the action via the relevant endpoint
• "open" or "打开" → query session state to get the data
• "drag/drop" or "拖拽" → send the edit command through SSE
• "preview in timeline" → show a text summary of current tracks
• "Export" or "导出" → run the 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 10-second video of a sunset over the ocean with calm waves" — concrete instructions get better results.

Max file size is 500MB. Stick to MP4, MOV, WebM, GIF for the smoothest experience.

Export as MP4 for widest compatibility across social platforms and devices.

Common Workflows

Quick edit: Upload → "generate a 10-second video of a sunset over the ocean with calm waves" → 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.