Video Subtitle Generator Online

v1.0.0

Turn a 3-minute YouTube tutorial recording into 1080p captioned video files just by typing what you need. Whether it's adding subtitles to videos without edi...

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for whitejohnk-26/video-subtitle-generator-online.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Video Subtitle Generator Online" (whitejohnk-26/video-subtitle-generator-online) from ClawHub.
Skill page: https://clawhub.ai/whitejohnk-26/video-subtitle-generator-online
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Required env vars: NEMO_TOKEN
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install video-subtitle-generator-online

ClawHub CLI

Package manager switcher

npx clawhub@latest install video-subtitle-generator-online
Security Scan
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OpenClawOpenClaw
Benign
high confidence
Purpose & Capability
Name/description (video subtitle + burn) match the behavior in SKILL.md: uploads, SSE-driven edits, render/export endpoints and a bearer token. Minor inconsistency: the registry metadata showed no required config paths, but the skill's YAML frontmatter references a config path (~/.config/nemovideo/). This is likely benign but worth clarifying.
Instruction Scope
Instructions limit actions to connecting to the nemo API, creating/using a session, uploading files, streaming SSE messages, polling state, and fetching render outputs. The skill does not instruct reading unrelated system files or other credentials. It does mention deriving an X-Skill-Platform header from install path detection (e.g., ~/.clawhub/) which implies checking the skill install location, a small operational detail rather than scope creep.
Install Mechanism
No install spec and no code files are present (instruction-only). That is the lowest-risk install model — nothing is downloaded or written to disk by the skill itself.
Credentials
Only one credential (NEMO_TOKEN) is requested and is necessary for Bearer auth to the described API. The SKILL.md also supports generating a short-lived anonymous token via the service, which reduces need for long-lived secrets. No unrelated secrets or multiple external credentials are requested.
Persistence & Privilege
always:false and normal model invocation are used. The skill does not request permanent agent-wide presence or modification of other skills. It asks to store session_id and use tokens for API calls (normal for this use case).
Assessment
This skill appears internally consistent for a cloud subtitle/render service, but exercise normal caution before installing: 1) The skill will upload any video you send to https://mega-api-prod.nemovideo.ai — confirm you are comfortable with that service's privacy and retention policies. 2) The skill asks for a NEMO_TOKEN; if you don't have one it will obtain an anonymous short-lived token for you. 3) There is no published source or homepage and the registry/frontmatter show a small metadata mismatch (config path present in the frontmatter but not in registry fields) — if provenance matters, ask the publisher for a repository or docs and verify the domain and API behavior before trusting sensitive or private videos. 4) If you need stricter guarantees, review network activity or run the service in an environment where you control uploads.

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

💬 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk97csdj0qw1g342f1t3hqwmbd984pzg7
101downloads
0stars
1versions
Updated 2w ago
v1.0.0
MIT-0

Getting Started

Ready when you are. Drop your video files here or describe what you want to make.

Try saying:

  • "add a 3-minute YouTube tutorial recording into a 1080p MP4"
  • "generate subtitles in English and Spanish and burn them into the video"
  • "adding subtitles to videos without editing software for YouTubers, 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.

Video Subtitle Generator Online — Generate and Burn Subtitles Automatically

Send me your video files 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 3-minute YouTube tutorial recording, type "generate subtitles in English and Spanish and burn them into the video", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: shorter clips under 5 minutes generate subtitles significantly faster.

Matching Input to Actions

User prompts referencing video subtitle generator online, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

User says...ActionSkip 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is video-subtitle-generator-online, X-Skill-Version comes from the version field, and X-Skill-Platform is detected from the install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, otherwise 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.

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 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

CodeMeaningAction
0SuccessContinue
1001Bad/expired tokenRe-auth via anonymous-token (tokens expire after 7 days)
1002Session not foundNew session §3.0
2001No creditsAnonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001Unsupported fileShow supported formats
4002File too largeSuggest compress/trim
400Missing X-Client-IdGenerate Client-Id and retry (see §1)
402Free plan export blockedSubscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429Rate limit (1 token/client/7 days)Retry in 30s once

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "generate subtitles in English and Spanish and burn them into the 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 platforms and devices.

Common Workflows

Quick edit: Upload → "generate subtitles in English and Spanish and burn them into the 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.

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