Text To Video Examples

Turn a 3-sentence product description into 1080p generated video clips just by typing what you need. Whether it's generating videos from written scripts or p...

Security Scan

The skill's instructions generally match a text→video service, but there are inconsistencies (metadata vs registry), an unknown source with no homepage, and runtime steps that can read/upload files and create/store an auth token — all of which warrant caution before installing.

Purpose & Capability

Name/description match the runtime instructions: the SKILL.md describes a remote video-rendering API and the skill requests a single service token (NEMO_TOKEN). However the package has no homepage, unknown source/owner, and the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata claimed no required config paths — this mismatch is unexplained.

Instruction Scope

The instructions direct the agent to call external API endpoints (session creation, SSE streaming, uploads, rendering) and to upload files via multipart (files=@/path). Upload operations necessarily require reading file paths the user supplies; that is expected for a video upload feature, but it also creates an exfiltration vector if the agent is allowed to read arbitrary files. The skill also instructs detecting install paths (~/.clawhub/, ~/.cursor/skills/) and reading this file's YAML frontmatter for attribution headers, which implies filesystem probing beyond the service's API. These behaviors are within a video service's plausible needs, but they increase risk and should be justified/limited.

Install Mechanism

This is an instruction-only skill with no install spec and no code files — nothing will be downloaded or written by an installer. That is lower risk compared to skills that fetch and extract remote archives.

Credentials

Only one env var is declared (NEMO_TOKEN), which is appropriate for a hosted video API. However, the SKILL.md describes generating an anonymous token via an API and treating the returned token as NEMO_TOKEN (100 credits, 7-day expiry), and the frontmatter references a config path (~/.config/nemovideo/) that the registry did not declare. The discrepancy between declared config paths and the SKILL.md metadata is a red flag. Also, because the skill accepts uploads, the token grants the service ability to act on uploaded data — ensure you understand what that token permits and how long it remains valid.

Persistence & Privilege

The skill is not always-included and uses normal autonomous invocation defaults. It will create and use session IDs and tokens for the remote API, which is expected. There is no claim it will modify other skills or system-wide settings. Monitor where it persists the anonymous token/session if it does so.

What to consider before installing

This skill plausibly implements a text→video API and only asks for a single service token, but exercise caution because: (1) the source and homepage are missing — you can't easily verify the provider; (2) the SKILL.md and registry metadata disagree about config paths (registry says none; the skill references ~/.config/nemovideo/), which is unexplained; (3) the runtime instructions allow uploading arbitrary files and instruct probing install paths, which could expose sensitive data if the agent is granted broad filesystem access. Before installing: verify the skill's provenance (official docs or vendor), confirm what NEMO_TOKEN can do and how long it lasts, avoid uploading sensitive files, prefer using an ephemeral or least-privilege token (revoke when done), and ask the skill author to explain the configPath discrepancy and precisely how/where tokens/sessions are stored.

Getting Started

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

Try saying:

• "convert a 3-sentence product description into a 1080p MP4"
• "turn this text into a 30-second explainer video with visuals and music"
• "generating videos from written scripts or prompts for marketers, content creators, educators"

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 Examples — Convert Text into Video Clips

Send me your text prompts and describe the result you want. The AI video creation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 3-sentence product description, type "turn this text into a 30-second explainer video with visuals and music", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter, clearer prompts produce more accurate and consistent video output.

Matching Input to Actions

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

Every API call needs Authorization: Bearer <NEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 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.

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)

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 → "turn this text into a 30-second explainer video with visuals and 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn this text into a 30-second explainer video with visuals and music" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across platforms and devices.