Text To Video Capcut Ai

Get AI generated videos ready to post, without touching a single slider. Upload your text prompts (TXT, DOCX, MP4, MOV, up to 200MB), say something like "tur...

Security Scan

The skill's technical requirements mostly match a text-to-video service (it asks for a single NEMO_TOKEN and calls nemovideo.ai endpoints), but the source is unknown and there is a minor branding/endpoint mismatch that warrants caution before uploading content or granting credentials.

Purpose & Capability

The skill claims 'CapCut' in its display name but all API endpoints and the required credential refer to 'nemovideo.ai' / NEMO_TOKEN; requiring a single service token is coherent for a cloud render API, but the naming mismatch and unknown source raise a legitimacy question.

Instruction Scope

SKILL.md contains detailed runtime instructions limited to authenticating, creating a session, uploading user media, streaming SSE events, polling render status, and returning download URLs—actions that align with a cloud text-to-video renderer. It explicitly instructs not to print tokens. The instructions do require uploading user files to the remote service, which is expected for this purpose but is sensitive behavior the user should be aware of.

Install Mechanism

No install spec and no code files (instruction-only) — lowest-risk install surface. Nothing is downloaded or written to disk by an installer per the manifest.

Credentials

The skill only requires one credential (NEMO_TOKEN), which is proportionate to a remote rendering API. It also documents how to obtain an anonymous token. That said, the token grants the skill the ability to upload user files and initiate renders on a third-party service, so users should treat the token as sensitive and confirm they trust the endpoint.

Persistence & Privilege

always is false and there are no requests to modify other skills or system-wide settings. The skill will store session IDs/tokens for operation (normal for such services). Autonomous invocation is allowed (platform default) but not by itself a red flag.

What to consider before installing

This instruction-only skill appears to be a thin client for a remote text-to-video service and asks for a single service token (NEMO_TOKEN). Before installing or using it: 1) verify you trust the operator/domain (mega-api-prod.nemovideo.ai) — the skill name references 'CapCut' but the backend is 'nemovideo.ai', which could be a rebrand or an unrelated service; 2) do not upload sensitive or confidential media unless you have reviewed the service's privacy/terms and are comfortable with third-party processing and storage; 3) prefer using the anonymous token flow (short-lived token) rather than providing long-lived credentials, and rotate/revoke tokens after use; 4) test with non-sensitive sample content first; and 5) if you require stronger assurance (e.g., corporate data), ask the skill author for publisher identity, a privacy policy, and a clear ownership/permission statement before proceeding.

Getting Started

Got text prompts to work with? Send it over and tell me what you need — I'll take care of the AI video creation.

Try saying:

• "convert a 150-word product description script into a 1080p MP4"
• "turn this script into a 30-second video with visuals and background music"
• "generating videos from written scripts or text prompts for TikTok creators"

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 CapCut AI — Convert Text Into AI Videos

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 150-word product description script, type "turn this script into a 30-second video with visuals and background music", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter scripts under 100 words produce more focused and faster results.

Matching Input to Actions

User prompts referencing text to video capcut ai, 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.

Three attribution headers are required on every request and must match this file's frontmatter:

Header	Value
X-Skill-Source	text-to-video-capcut-ai
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-detect: clawhub / cursor / unknown from install path

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 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 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 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, MP4, MOV for the smoothest experience.

Export as MP4 for widest compatibility across social 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.