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Ai Subtitle Davinci

v1.0.0

add video clips into captioned video files with this skill. Works with MP4, MOV, AVI, MKV files up to 500MB. video editors and YouTubers use it for adding AI...

0· 34·0 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 susan4731-wilfordf/ai-subtitle-davinci.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Ai Subtitle Davinci" (susan4731-wilfordf/ai-subtitle-davinci) from ClawHub.
Skill page: https://clawhub.ai/susan4731-wilfordf/ai-subtitle-davinci
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 ai-subtitle-davinci

ClawHub CLI

Package manager switcher

npx clawhub@latest install ai-subtitle-davinci
Security Scan
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medium confidence
Purpose & Capability
The skill's stated purpose (auto-captioning and rendering DaVinci exports) aligns with the documented API calls (upload, render, credits, session). Requesting a NEMO_TOKEN is coherent for a hosted processing API. However, the SKILL.md frontmatter mentions a config path (~/.config/nemovideo/) while the registry metadata lists no required config paths — an internal inconsistency worth clarifying.
Instruction Scope
Instructions focus on connecting to a remote API, starting a session, uploading user-supplied video files, handling SSE, and polling render status — all within the declared purpose. They direct the agent to read the skill's own YAML frontmatter and to detect an install path to produce attribution headers; that implies the agent may inspect its runtime/install path. The skill also instructs generating an anonymous token via the API when no NEMO_TOKEN is present. There are no instructions to read unrelated user files or secrets, but uploads will transmit user media to the external domain.
Install Mechanism
This is an instruction-only skill with no install spec or code to download — lowest install risk. Nothing will be written to disk by an installer step from this package itself.
Credentials
Only one credential is declared (NEMO_TOKEN), which is appropriate for a hosted API. However: (1) the frontmatter in SKILL.md also lists a config path (~/.config/nemovideo/) not declared elsewhere; (2) the anonymous-token flow advises the agent to generate and adopt a token (100 credits, 7-day expiry) which could result in the agent holding or persisting credentials; and (3) that token grants access to the remote account and uploaded content. The level of access is expected for the service but you should treat the token as sensitive.
Persistence & Privilege
The skill does not request always:true and does not explicitly require system-wide privileges. It instructs the agent to 'save session_id' and to use/store tokens; where and how those are stored is unspecified and could result in persistent credentials or session state. The agent's autonomous invocation is allowed (platform default), so a compromised token or service could be used without explicit user action unless the platform enforces additional guards.
What to consider before installing
This skill appears to send uploaded video files to a third‑party service (mega-api-prod.nemovideo.ai) and needs a NEMO_TOKEN (or will request an anonymous token) to operate. Before installing or using it: 1) Verify you trust the nemovideo domain and its privacy/retention policy because your videos and audio will be transmitted off your machine. 2) Clarify where tokens and session_ids are stored (ephemeral memory vs written to disk) and whether the skill will persist them. 3) Ask the publisher for a homepage or source code (none provided) and for an explanation of the configPath mention (~/.config/nemovideo/) found in SKILL.md. 4) If your media is sensitive, prefer a local/offline tool rather than a cloud render service. If you still want to use it, limit the token scope where possible and rotate/revoke tokens after use.

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

Runtime requirements

🎬 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk979j60j748px805pg8b0m096s85kd2d
34downloads
0stars
1versions
Updated 1d ago
v1.0.0
MIT-0

Getting Started

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

Try saying:

  • "add a 3-minute DaVinci Resolve project export into a 1080p MP4"
  • "automatically generate and burn in subtitles for my DaVinci edited video"
  • "adding AI-generated subtitles to DaVinci Resolve edited videos for video editors and YouTubers"

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.

AI Subtitle DaVinci — Auto-Caption DaVinci Edited Videos

Send me your video clips 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 DaVinci Resolve project export, type "automatically generate and burn in subtitles for my DaVinci edited video", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: export a clean MP4 from DaVinci before uploading for the most accurate subtitle sync.

Matching Input to Actions

User prompts referencing ai subtitle davinci, 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.

Skill attribution — read from this file's YAML frontmatter at runtime:

  • X-Skill-Source: ai-subtitle-davinci
  • 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.

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 "automatically generate and burn in subtitles for my DaVinci edited video" — concrete instructions get better results.

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

Export from DaVinci as H.264 MP4 for the best compatibility and fastest processing.

Common Workflows

Quick edit: Upload → "automatically generate and burn in subtitles for my DaVinci edited 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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