Text To Video Download

Turn a 150-word product description paragraph into 1080p downloadable MP4 videos just by typing what you need. Whether it's turning written content into down...

Security Scan

The skill mostly does what it says (send text and files to a cloud video-rendering API using a single NEMO_TOKEN), but there are small mismatches and filesystem-read instructions (install-path/config detection) that are unnecessary for the stated purpose and warrant caution.

Purpose & Capability

Name/description, the listed API endpoints, and the single required env var (NEMO_TOKEN) align with a text→video cloud rendering service. However the SKILL.md frontmatter includes a config path (~/.config/nemovideo/) and instructions to detect the agent's install path to set X-Skill-Platform; the registry metadata reported no required config paths. That mismatch is unexplained and not clearly needed for core functionality (producing downloads).

Instruction Scope

The SKILL.md contains explicit runtime instructions to call external HTTPS APIs (session creation, SSE, upload, render polling), generate an anonymous token if NEMO_TOKEN is missing, save session_id, and stream SSE text to users. Those actions fit the stated purpose. It also directs the agent to read the skill's YAML frontmatter and to detect the agent's install path (~/.clawhub/, ~/.cursor/skills/, else unknown) to populate an attribution header — instructions that require probing the filesystem and are not strictly necessary for video rendering.

Install Mechanism

There is no install spec and no code files; the skill is instruction-only. That is the lowest-risk install model — nothing will be downloaded or written by an installer step.

Credentials

Only one credential is requested (NEMO_TOKEN), which is proportional to a cloud API integration. However the frontmatter's configPaths entry (~/.config/nemovideo/) and the runtime requirement to detect install paths could allow access to local config files. The skill also instructs generating and storing session tokens. The extra filesystem access is not well justified by the described feature set.

Persistence & Privilege

always is false and there is no install-time persistence. The skill does instruct saving session_id for ongoing interactions (normal for a session-based API). Autonomous invocation (disable-model-invocation=false) is the platform default and is not by itself flagged.

What to consider before installing

This skill appears to implement a cloud text→video workflow and only needs a NEMO_TOKEN (or it can request an anonymous token). Before installing, consider: 1) The API domain (mega-api-prod.nemovideo.ai) is external and will receive any uploaded files and text — don't send sensitive data unless you trust the service. 2) The SKILL.md asks the agent to read the skill frontmatter and detect your agent's install path and a local config path (~/.config/nemovideo/) to set attribution headers; that requires filesystem access and seems unnecessary for basic operation. Ask the author why install-path detection and that config path are needed and whether the skill will read or transmit any local files. 3) If you proceed, prefer using an ephemeral/limited token (or the anonymous token flow) and test with non-sensitive inputs first. If you require higher assurance, request the author provide a version of the instructions that does not probe local config paths or that documents exactly what files are read.

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"
• "convert this blog intro into a"

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.

Text to Video Download — Convert Text Into Downloadable Videos

This tool takes your 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 convert this blog intro into a 30-second video and download it as MP4 — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter text inputs under 100 words produce faster and more focused video outputs.

Matching Input to Actions

User prompts referencing text to video download, 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.

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

• X-Skill-Source: text-to-video-download
• 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.

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.

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 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)

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

Common Workflows

Quick edit: Upload → "convert this blog intro into a 30-second video and download it as MP4" → 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "convert this blog intro into a 30-second video and download it as MP4" — concrete instructions get better results.

Max file size is 500MB. Stick to TXT, DOCX, PDF, copied text for the smoothest experience.

Export as MP4 for widest compatibility across platforms and devices.