Youtube Ai Subtitle Generator

Get captioned YouTube videos ready to post, without touching a single slider. Upload your YouTube videos (MP4, MOV, AVI, WebM, up to 500MB), say something li...

Security Scan

The skill's requests and instructions are generally consistent with a cloud-based YouTube subtitle/rendering service — it asks only for a single service token and instructs network calls to that service — but it will send user videos to an external API and auto-acquire anonymous tokens if none are provided.

Purpose & Capability

Name/description (YouTube subtitle generation) map to the declared requirement (NEMO_TOKEN) and the documented API endpoints on mega-api-prod.nemovideo.ai. The single required env var (NEMO_TOKEN) is appropriate for a third‑party video-processing backend.

Instruction Scope

SKILL.md instructs the agent to upload videos and drive remote rendering via many explicit endpoints — all consistent with the stated purpose. It also instructs the agent to read the skill's YAML frontmatter and detect the agent install path to populate attribution headers; that implies the agent will inspect its own files/paths. The instructions will transmit user video files and metadata to the external nemovideo API (expected for this skill).

Install Mechanism

No install spec and no code files — instruction-only skill. That limits on-disk changes and reduces installation risk.

Credentials

Only NEMO_TOKEN is required and is the declared primary credential, which fits a cloud service. The skill will auto-acquire an anonymous token from the service if NEMO_TOKEN is absent (100 free credits, 7-day expiry) — this behavior is documented in SKILL.md but means the agent may call the auth endpoint automatically.

Persistence & Privilege

always is false and the skill does not request system-wide configuration changes or other skills' credentials. Autonomous invocation is allowed (platform default) but is not combined with other privilege concerns.

Assessment

This skill will upload your video files and related metadata to an external service (mega-api-prod.nemovideo.ai) to run GPU-based subtitle generation and rendering. It requires (or will obtain) a NEMO_TOKEN bearer token; if you don't provide one it will call the service to get an anonymous token (100 free credits, 7-day expiry). The skill also reads its own frontmatter / install path to add attribution headers. Before installing, confirm you trust nemovideo.ai for processing and storing your video content and check their privacy/terms. Avoid sending sensitive or private videos unless you accept that they will be transmitted to that remote service. If you want stronger control, provide your own NEMO_TOKEN or disable the skill when not in use.

Getting Started

Ready when you are. Drop your YouTube videos here or describe what you want to make.

Try saying:

• "generate a 10-minute YouTube tutorial video into a 1080p MP4"
• "generate subtitles in English and Spanish for my YouTube video"
• "adding AI-generated subtitles to YouTube videos for YouTubers"

Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:

• Generate a UUID as client identifier
• POST https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
• Extract data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

YouTube AI Subtitle Generator — Generate Subtitles for YouTube Videos

Send me your YouTube videos and describe the result you want. The AI subtitle generation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 10-minute YouTube tutorial video, type "generate subtitles in English and Spanish for my YouTube video", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: shorter video segments produce more accurate subtitle timing.

Matching Input to Actions

User prompts referencing youtube ai subtitle 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: youtube-ai-subtitle-generator
• 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.

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)

Common Workflows

Quick edit: Upload → "generate subtitles in English and Spanish for my YouTube video" → Download MP4. Takes 30-60 seconds 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 "generate subtitles in English and Spanish for my YouTube video" — concrete instructions get better results.

Max file size is 500MB. Stick to MP4, MOV, AVI, WebM for the smoothest experience.

Export as MP4 for widest compatibility across YouTube and other platforms.