Caption Generator From Video

v1.0.0

Skip the learning curve of professional editing software. Describe what you want — add captions in English and Spanish to my video — and get captioned video...

0· 65·0 current·0 all-time

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for tk8544-b/caption-generator-from-video.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Caption Generator From Video" (tk8544-b/caption-generator-from-video) from ClawHub.
Skill page: https://clawhub.ai/tk8544-b/caption-generator-from-video
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 caption-generator-from-video

ClawHub CLI

Package manager switcher

npx clawhub@latest install caption-generator-from-video
Security Scan
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medium confidence
Purpose & Capability
The skill is a cloud video captioning frontend and requires a NEMO_TOKEN for the nemo-video backend — that aligns with its purpose. However, the declared config path (~/.config/nemovideo/) appears in metadata but is never referenced in the runtime instructions, which is an unexplained metadata/instruction mismatch.
Instruction Scope
SKILL.md instructs the agent to upload user video files and interact with the nemo API (session creation, SSE, upload, export), which is expected for a remote render/caption service. The instructions do not ask the agent to read unrelated local files or other environment variables beyond NEMO_TOKEN. It explicitly says not to display raw tokens to users.
Install Mechanism
There is no install spec and no code files; this is instruction-only, which is the lowest-risk install mechanism.
Credentials
Requesting a single NEMO_TOKEN is proportionate for a service that requires authenticated uploads. Oddly, the instructions include an anonymous-token endpoint to obtain a token automatically if NEMO_TOKEN isn't set, making the env var optional in practice — this mismatch between declared required env vars and runtime behavior should be clarified. The declared configPath is also unnecessary per the instructions.
Persistence & Privilege
The skill does not request always:true and has no install-time persistence. It will create temporary session tokens and submit jobs to a remote service, which is expected for its function and does not escalate privileges on the host.
Assessment
This skill appears to be a front-end for a cloud captioning/rendering service and will upload whatever video files you give it to mega-api-prod.nemovideo.ai. Consider these points before installing: - Privacy: Uploaded videos (and their audio) go to an external service; do not upload sensitive content unless you trust the service and its terms. - Credentials: The skill uses NEMO_TOKEN for Authorization. It can also obtain a 7-day anonymous token automatically; decide if you want to provide your own long-lived token or rely on anonymous tokens. Treat any token as a secret. - Metadata mismatch: The skill metadata lists a config path (~/.config/nemovideo/) even though the runtime instructions never read local config — ask the publisher why that path is declared and where session/token data will be stored. - Billing/credits: The skill mentions credits; confirm whether processing beyond anonymous limits requires registration or payment and how you’ll be notified. - Verification: Because the skill is instruction-only and has no official homepage, verify the backend domain and the publisher (if possible) before sending private content. If you need more assurance, ask the publisher for a privacy policy, terms, or an official homepage.

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

Runtime requirements

💬 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk975vwc9yzczndt35bvc4by25x8509bb
65downloads
0stars
1versions
Updated 1w ago
v1.0.0
MIT-0

Getting Started

Share your video files and I'll get started on AI caption generation. Or just tell me what you're thinking.

Try saying:

  • "generate my video files"
  • "export 1080p MP4"
  • "add captions in English and Spanish"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

  1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
  2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer <token>, Content-Type: application/json, and body {"task_name":"project","language":"<detected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

Caption Generator From Video — Generate Captions From Any Video

Send me your video files and describe the result you want. The AI caption generation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 3-minute interview recorded on a smartphone, type "add captions in English and Spanish to my 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 process significantly faster.

Matching Input to Actions

User prompts referencing caption generator from video, 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.

All calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:

  1. SessionPOST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"<lang>"}. Gives you a session_id.
  2. Chat (SSE)POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.
  3. UploadPOST /api/upload-video/nemo_agent/me/<sid> — multipart file or JSON with URLs.
  4. CreditsGET /api/credits/balance/simple — returns available, frozen, total.
  5. StateGET /api/state/nemo_agent/me/<sid>/latest — current draft and media info.
  6. ExportPOST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/<id> every 30s for completed status and download URL.

Formats: 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: caption-generator-from-video
  • 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.

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)

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

SSE Event Handling

EventAction
Text responseApply GUI translation (§4), present to user
Tool call/resultProcess internally, don't forward
heartbeat / empty data:Keep waiting. Every 2 min: "⏳ Still working..."
Stream closesProcess 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.

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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "add captions in English and Spanish to my 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.

Common Workflows

Quick edit: Upload → "add captions in English and Spanish to my 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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