Text To Video Io

Get AI generated videos ready to post, without touching a single slider. Upload your text prompts (TXT, DOCX, PDF, SRT, up to 200MB), say something like "tur...

Security Scan

The skill's requested credential (NEMO_TOKEN) and API calls match a text-to-video service, but there are small inconsistencies and a few instruction-time actions (filesystem detection, example local-file uploads, anonymous token generation) that broaden its scope beyond what's explicitly stated.

Purpose & Capability

The declared primary environment variable (NEMO_TOKEN) and the documented API endpoints are coherent with a cloud text→video service. However the SKILL.md frontmatter also lists a config path (~/.config/nemovideo/) that the registry metadata did not list, which is an internal inconsistency worth clarifying.

Instruction Scope

Runtime instructions ask the agent to: detect install path (reading local paths), read the skill's YAML frontmatter for headers, and include an example of multipart upload using files=@/path. These items imply filesystem access and automatic token generation/management beyond just relaying user-uploaded files. While each action can be reasonable for this service, they expand the agent's runtime scope and could lead to unintended local file access if not constrained.

Install Mechanism

No install spec and no code files — instruction-only skills present a lower install-time risk because nothing is downloaded or written to disk by an installer.

Credentials

Only NEMO_TOKEN is required, which fits the described API usage. The skill also instructs creating an anonymous token when none is present — reasonable for unauthenticated use — but this behavior means the skill will make outbound network calls to obtain credentials and may persist/use that token.

Persistence & Privilege

always is false and there is no instruction to modify other skills or system-wide config. The skill requests only session-level interaction with the backend, not elevated platform privileges.

What to consider before installing

This skill appears to really target a text→video backend and only asks for a single API token, but you should: (1) verify you trust the API host (mega-api-prod.nemovideo.ai) and the developer because there is no source/homepage listed; (2) confirm you are comfortable the agent may read install paths or the skill file frontmatter (the SKILL.md directs that); (3) be cautious about letting the agent access arbitrary local files — when uploading, prefer sending files through the UI rather than letting the agent reference local filesystem paths; (4) note the registry/frontmatter mismatch about a config path (~/.config/nemovideo/) and ask the maintainer to clarify; (5) if you need stronger assurance, request the skill's source or a homepage and avoid installing until you can inspect how tokens are stored/used.

Getting Started

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

Try saying:

• "convert my text prompts"
• "export 1080p MP4"
• "turn this script into a 30-second"

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 IO — Convert Text Into AI Videos

Drop your text prompts in the chat and tell me what you need. I'll handle the AI video creation on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 200-word product description, ask for turn this script into a 30-second video with visuals and background music, and about 1-2 minutes later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter, clearer prompts produce more accurate and consistent visuals.

Matching Input to Actions

User prompts referencing text to video io, 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.

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

• X-Skill-Source: text-to-video-io
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)

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 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

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

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 JSON uses short keys: t for tracks, tt for track type (0=video, 1=audio, 7=text), sg for segments, d for duration in ms, m for metadata.

Example timeline summary:

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 script into a 30-second video with visuals and background music" — 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 social and web platforms.

Common Workflows

Quick edit: Upload → "turn this script into a 30-second video with visuals and background music" → 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.