Text To Video Making

Skip the learning curve of professional editing software. Describe what you want — turn this blog intro into a 30-second explainer video with visuals and voi...

Security Scan

The skill's stated purpose (convert text to video) aligns with its runtime instructions and required credential (NEMO_TOKEN); nothing obviously malicious is present, though there are a few minor inconsistencies and privacy/clarity issues to confirm before installation.

Purpose & Capability

The skill claims to call a remote AI video service and the SKILL.md documents API endpoints, session creation, upload, render, and export flows. Requesting an API token (NEMO_TOKEN) is consistent with that purpose.

Instruction Scope

Instructions are focused on interacting with the remote nemovideo API (auth, session creation, uploads, SSE for generation, render/export). It also instructs generating an anonymous client id when no token is present, and adding attribution headers (X-Skill-Source/Version/Platform). The attribution header logic references local install paths to detect platform, which is a minor privacy detail but not out-of-scope for the skill's functionality.

Install Mechanism

There is no install specification and no code files (instruction-only). This is the lowest-risk install model — nothing is written or downloaded by the skill itself.

Credentials

The only declared required credential is NEMO_TOKEN, which fits the service. However, the SKILL.md frontmatter metadata also lists a config path (~/.config/nemovideo/) not reflected in the registry summary (which reported no required config paths). This inconsistency should be clarified: does the skill read or write that config directory? If it does, that increases the scope of local access and privacy implications.

Persistence & Privilege

The skill is not marked always:true and does not request elevated or permanent presence. It does not instruct modifying other skills or global agent settings. Autonomous invocation is allowed (default) but not combined with unusual privileges.

Assessment

This skill appears to do what it says: it talks to a remote nemovideo API and needs a NEMO_TOKEN. Before installing, confirm the following: (1) Verify the domain mega-api-prod.nemovideo.ai is the official service you expect. (2) Ask the skill author whether the config path (~/.config/nemovideo/) is actually accessed or written; if yes, understand what is stored there. (3) Prefer using a short-lived/anonymous token if you don't want to supply a permanent NEMO_TOKEN; the skill supports creating a temporary anonymous token. (4) Avoid uploading sensitive or private documents to the service unless you trust its privacy policy. (5) If you are concerned about the attribution headers or local install-path detection, request clarification or a version that omits platform detection. Clarifying these points will raise confidence from medium to high.

Getting Started

Send me your written text prompts and I'll handle the AI video creation. Or just describe what you're after.

Try saying:

• "convert a 150-word product description paragraph into a 1080p MP4"
• "turn this blog intro into a 30-second explainer video with visuals and voiceover"
• "converting written content into short videos for social media or presentations for marketers, content creators, educators"

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

• Generate a UUID as client identifier
• POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
• The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

Text to Video Making — Convert Text into Shareable Videos

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

Say you have a 150-word product description paragraph and want to turn this blog intro into a 30-second explainer video with visuals and voiceover — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter, clearer text produces more accurate scene generation.

Matching Input to Actions

User prompts referencing text to video making, 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 text-to-video-making, 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 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 "turn this blog intro into a 30-second explainer video with visuals and voiceover" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across platforms and devices.

Common Workflows

Quick edit: Upload → "turn this blog intro into a 30-second explainer video with visuals and voiceover" → Download MP4. Takes 1-2 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.