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Caption Generator Davinci

作者 mhogan2013-9 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install caption-generator-davinci
功能描述
add video clips into captioned video files with this skill. Works with MP4, MOV, AVI, MKV files up to 500MB. video editors use it for adding auto-synced capt...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "add a 2-minute DaVinci Resolve export into a 1080p MP4"
  • "add auto-generated captions synced to speech in English"
  • "adding auto-synced captions to DaVinci Resolve videos for video editors"

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: \x3Cuuid>. 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.

Caption Generator DaVinci — Add Captions to DaVinci Videos

Drop your video clips in the chat and tell me what you need. I'll handle the AI caption generation on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 2-minute DaVinci Resolve export, ask for add auto-generated captions synced to speech in English, and about 30-60 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter clips under 3 minutes process significantly faster.

Matching Input to Actions

User prompts referencing caption generator davinci, 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.

Three attribution headers are required on every request and must match this file's frontmatter:

Header Value
X-Skill-Source caption-generator-davinci
X-Skill-Version frontmatter version
X-Skill-Platform auto-detect: clawhub / cursor / unknown from install path

Include Authorization: Bearer \x3CNEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

API base: https://mega-api-prod.nemovideo.ai

Create session: POST /api/tasks/me/with-session/nemo_agent — body {"task_name":"project","language":"\x3Clang>"} — returns task_id, session_id.

Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"\x3Csid>","new_message":{"parts":[{"text":"\x3Cmsg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.

Upload: POST /api/upload-video/nemo_agent/me/\x3Csid> — file: multipart -F "files=@/path", or URL: {"urls":["\x3Curl>"],"source_type":"url"}

Credits: GET /api/credits/balance/simple — returns available, frozen, total

Session state: GET /api/state/nemo_agent/me/\x3Csid>/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_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/\x3Cid> 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.

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.

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend says You do
"click [button]" / "点击" Execute via API
"open [panel]" / "打开" Query session state
"drag/drop" / "拖拽" Send edit via SSE
"preview in timeline" Show track summary
"Export button" / "导出" Execute export workflow

Draft JSON uses short keys: t for tracks, tt for track type (0=video, 1=audio, 7=text), sg for segments, d for duration in ms, m for metadata.

Example timeline summary:

Timeline (3 tracks): 1. Video: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)

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=\x3Cid>, 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 auto-generated captions synced to speech in English" — concrete instructions get better results.

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

Export as MP4 from DaVinci Resolve before uploading for best compatibility.

Common Workflows

Quick edit: Upload → "add auto-generated captions synced to speech in English" → 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.

安全使用建议
This looks purpose-aligned for cloud video captioning. Before installing, make sure you are comfortable sending your video files to mega-api-prod.nemovideo.ai and using or generating a NEMO_TOKEN. Avoid uploading sensitive footage unless you trust the provider.
功能分析
Type: OpenClaw Skill Name: caption-generator-davinci Version: 1.0.0 The skill is a functional integration for a cloud-based video captioning service. It provides the AI agent with detailed instructions for managing authentication tokens, session states, and file uploads to the 'nemovideo.ai' API. The behavior, including the use of a configuration directory (~/.config/nemovideo/) and automated token acquisition, is transparently documented and strictly aligned with the stated purpose of processing video files on cloud GPUs. No indicators of data exfiltration, malicious execution, or harmful prompt injection were found.
能力评估
Purpose & Capability
The visible instructions consistently describe cloud-based captioning/rendering for uploaded videos, which matches the skill description.
Instruction Scope
The skill lets the remote backend guide workflow steps such as editing and exporting through API actions; this is purpose-aligned but should remain limited to user-requested video operations.
Install Mechanism
There is no local install spec or code to review, but the registry lists the source as unknown and no homepage is provided.
Credentials
Use of NEMO_TOKEN and cloud upload/render APIs is proportionate for this captioning service, but users should understand that their media is processed by the external provider.
Persistence & Privilege
The artifacts show temporary cloud session/job IDs, but no evidence of local background persistence, privilege escalation, or autonomous activity outside the video workflow.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install caption-generator-davinci
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /caption-generator-davinci 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release of Caption Generator DaVinci - Add captions to DaVinci Resolve video exports using an automated cloud-based pipeline. - Supports MP4, MOV, AVI, MKV files up to 500MB; outputs 1080p MP4 with auto-synced captions. - Handles uploads, credit tracking, export/downloads, and session management via cloud API. - Users can interact via chat to upload video, add captions, check credits, and export results. - Jobs process on GPU (typically 30–90 seconds); exports ready for download. - Automatic setup: free tokens available for new users, session creation handled transparently.
元数据
Slug caption-generator-davinci
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Caption Generator Davinci 是什么?

add video clips into captioned video files with this skill. Works with MP4, MOV, AVI, MKV files up to 500MB. video editors use it for adding auto-synced capt... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 60 次。

如何安装 Caption Generator Davinci?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install caption-generator-davinci」即可一键安装,无需额外配置。

Caption Generator Davinci 是免费的吗?

是的,Caption Generator Davinci 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Caption Generator Davinci 支持哪些平台?

Caption Generator Davinci 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Caption Generator Davinci?

由 mhogan2013-9(@mhogan2013-9)开发并维护,当前版本 v1.0.0。

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