Ai Text Video Generator

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

Security Scan

The skill's behavior largely matches a text→video cloud service (it needs a NEMO_TOKEN and calls nemovideo endpoints) but there are a few incoherences and scope-creep details you should review before installing.

Purpose & Capability

Name/description match required network calls and a service token (NEMO_TOKEN). However, the SKILL.md metadata requests a config path (~/.config/nemovideo/) and instructs detecting install path and reading this file's YAML frontmatter for attribution — these file-system checks are not strictly necessary for basic text→video functionality and are inconsistent with the published registry 'Required config paths: none'.

Instruction Scope

Runtime instructions include normal API flows (token use/renewal, session creation, upload, SSE polling, render/export). But the skill explicitly tells the agent to read its own YAML frontmatter and to detect the install path (e.g., ~/.clawhub/ or ~/.cursor/skills/) to set attribution headers — that requires file-system/installation-path access beyond just calling the external API and could reveal local environment/paths. Also the SKILL.md asks to 'keep the technical details out of the chat', which reduces transparency about what is sent to the backend.

Install Mechanism

Instruction-only skill with no install spec or code files — nothing will be downloaded or written to disk by an installer. This is lower risk from a supply-chain/install perspective.

Credentials

Only one declared credential (NEMO_TOKEN), which is appropriate for a cloud video API. The SKILL.md also defines an anonymous-token flow that generates a client UUID and fetches a temporary token from the external endpoint — expected but worth noting. The mismatch between registry metadata (no config paths) and the SKILL.md's metadata (includes ~/.config/nemovideo/) is an incoherence to clarify.

Persistence & Privilege

Skill is not forced-always; autonomous invocation is allowed (platform default). The skill does create ephemeral sessions/tokens on the backend and may leave server-side render jobs running if a client disconnects (noted in docs) — expected for this type of service and not an escalation of local privileges.

What to consider before installing

What to consider before installing: - This skill will call an external service (mega-api-prod.nemovideo.ai) and will upload any files or text you give it — don't send sensitive or private content unless you trust that service and have reviewed its terms/privacy. - The skill expects a NEMO_TOKEN; if you don't provide one it will obtain an anonymous token by POSTing a generated client UUID to the vendor endpoint (so network contact happens either way). Use a disposable token if you want to limit exposure. - The SKILL.md asks the agent to read the skill file's YAML frontmatter and detect install paths to set attribution headers — that means the agent will look at installation location and local skill metadata. If you are uncomfortable with any local filesystem reads, ask the author why this is needed or decline installation. - There is an inconsistency between the registry summary (no required config paths) and the SKILL.md metadata (mentions ~/.config/nemovideo/). Ask the publisher to clarify which local paths the skill will access. - Because this is instruction-only (no code install), the main risk is data exfiltration over the network, not supply-chain code execution. To be safer, test with non-sensitive inputs first and verify the actual requests (headers, endpoints) the agent makes, and consider using an anonymous/disposable token or network isolation if possible.

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:

• "generate my text prompts"
• "export 1080p MP4"
• "turn this blog post intro into"

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.

AI Text Video Generator — Convert Text Into Shareable 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 and want to turn this blog post intro into a 30-second video with visuals and voiceover — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter text inputs under 200 words produce faster and more focused videos.

Matching Input to Actions

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

Include Authorization: Bearer <NEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

Error Codes

• 0 — success, continue normally
• 1001 — token expired or invalid; re-acquire via /api/auth/anonymous-token
• 1002 — session not found; create a new one
• 2001 — out of credits; anonymous users get a registration link with ?bind=<id>, registered users top up
• 4001 — unsupported file type; show accepted formats
• 4002 — file too large; suggest compressing or trimming
• 400 — missing X-Client-Id; generate one and retry
• 402 — free plan export blocked; not a credit issue, subscription tier
• 429 — rate limited; wait 30s and retry 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.

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)

Common Workflows

Quick edit: Upload → "turn this blog post intro into a 30-second 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn this blog post intro into a 30-second video with visuals and voiceover" — 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 social platforms and websites.