Subtitle Generator Davinci Resolve

v1.0.0

Get captioned video files ready to post, without touching a single slider. Upload your video files (MP4, MOV, AVI, MKV, up to 500MB), say something like "gen...

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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 mory128/subtitle-generator-davinci-resolve.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Subtitle Generator Davinci Resolve" (mory128/subtitle-generator-davinci-resolve) from ClawHub.
Skill page: https://clawhub.ai/mory128/subtitle-generator-davinci-resolve
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 subtitle-generator-davinci-resolve

ClawHub CLI

Package manager switcher

npx clawhub@latest install subtitle-generator-davinci-resolve
Security Scan
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medium confidence
Purpose & Capability
The skill claims to be a cloud-based subtitle/renderer and all runtime instructions (session creation, upload, export, polling) match that purpose. It legitimately requires a service token (NEMO_TOKEN). Minor inconsistency: the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) in metadata, but the registry metadata shown earlier reported no required config paths — this mismatch should be clarified.
Instruction Scope
The SKILL.md instructs the agent to upload user video files and to POST to external endpoints at mega-api-prod.nemovideo.ai, create sessions, use SSE, and poll for render results — all within scope for a cloud render/subtitle tool. It does not instruct reading unrelated local files or environment variables beyond NEMO_TOKEN. Important privacy implication: user video/audio files are sent to a third-party cloud service; users should be aware of that.
Install Mechanism
Instruction-only skill with no install spec and no binaries — lowest installation risk. Nothing is downloaded or written to disk by the skill itself.
Credentials
Only NEMO_TOKEN is required as the primary credential, which is proportionate for authenticating to the described backend. Caveats: the SKILL.md also references a config path in its frontmatter (potentially implying local config usage) which wasn't declared elsewhere; confirm whether the skill will read files under ~/.config/nemovideo/ before installing. Also, any token you provide grants the skill the ability to act as that identity against the external API, so ensure the token is scoped appropriately.
Persistence & Privilege
The skill is not always-enabled and does not request elevated or persistent system privileges. It does not attempt to modify other skills or system-wide configs in the instructions provided.
Assessment
This skill sends your uploaded videos and audio to an external service (mega-api-prod.nemovideo.ai) for subtitle generation and rendering. Before using it: (1) Confirm you trust that domain and its privacy/retention policy because media will leave your machine. (2) Provide a purpose-scoped or ephemeral NEMO_TOKEN (do not reuse highly privileged secrets). (3) Ask the publisher for a homepage or source code (none is listed) and clarification about the ~ /.config/nemovideo/ path (the registry metadata and the SKILL.md disagree). (4) If you need stronger assurance, request sample API request/response logs or a developer repo to audit how tokens and uploads are handled.

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

Runtime requirements

🎬 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk97aqemp8mqj25sf4e1v9fbjfd84pq9k
98downloads
0stars
1versions
Updated 2w ago
v1.0.0
MIT-0

Getting Started

Send me your video files and I'll handle the subtitle generation. Or just describe what you're after.

Try saying:

  • "generate a 3-minute interview clip exported from DaVinci Resolve into a 1080p MP4"
  • "generate subtitles for my DaVinci Resolve video and export as MP4 with burned-in captions"
  • "adding subtitles to DaVinci Resolve edited videos for video editors"

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

  • Generate a UUID as client identifier
  • POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
  • The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

Subtitle Generator for DaVinci Resolve — Auto-generate captions for videos

This tool takes your video files and runs subtitle generation through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 3-minute interview clip exported from DaVinci Resolve and want to generate subtitles for my DaVinci Resolve video and export as MP4 with burned-in captions — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: export your DaVinci Resolve timeline as MP4 first, then upload for fastest subtitle processing.

Matching Input to Actions

User prompts referencing subtitle generator davinci resolve, 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is subtitle-generator-davinci-resolve, 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).

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.

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 "generate subtitles for my DaVinci Resolve video and export as MP4 with burned-in captions" — concrete instructions get better results.

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

Export from DaVinci Resolve as H.264 MP4 for the best compatibility with subtitle processing.

Common Workflows

Quick edit: Upload → "generate subtitles for my DaVinci Resolve video and export as MP4 with burned-in captions" → 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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