功能描述

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

使用说明 (SKILL.md)

Getting Started

Got video files to work with? Send it over and tell me what you need — I'll take care of the AI subtitle generation.

Try saying:

"add a 10-minute MP4 lecture recording into a 1080p MP4"
"generate and embed subtitles into my video so I can play it with captions in VLC"
"adding burned-in subtitles to videos for VLC playback for casual viewers and students"

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.

AI Subtitle in VLC — Generate and Embed Video Subtitles

Name: Ai Subtitle In Vlc
Author: susan4731-wilfordf

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

Say you have a 10-minute MP4 lecture recording and want to generate and embed subtitles into my video so I can play it with captions in VLC — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: burning subtitles into the video means they show automatically in VLC without any extra setup.

Matching Input to Actions

User prompts referencing ai subtitle in vlc, 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.

Base URL: https://mega-api-prod.nemovideo.ai

Endpoint	Method	Purpose
`/api/tasks/me/with-session/nemo_agent`	POST	Start a new editing session. Body: `{"task_name":"project","language":"\x3Clang>"}`. Returns `session_id`.
`/run_sse`	POST	Send a user message. Body includes `app_name`, `session_id`, `new_message`. Stream response with `Accept: text/event-stream`. Timeout: 15 min.
`/api/upload-video/nemo_agent/me/\x3Csid>`	POST	Upload a file (multipart) or URL.
`/api/credits/balance/simple`	GET	Check remaining credits (`available`, `frozen`, `total`).
`/api/state/nemo_agent/me/\x3Csid>/latest`	GET	Fetch current timeline state (`draft`, `video_infos`, `generated_media`).
`/api/render/proxy/lambda`	POST	Start export. Body: `{"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}`. Poll status every 30s.

Accepted file types: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

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

Header	Value
`X-Skill-Source`	`ai-subtitle-in-vlc`
`X-Skill-Version`	frontmatter `version`
`X-Skill-Platform`	auto-detect: `clawhub` / `cursor` / `unknown` from install path

Every API call needs Authorization: Bearer \x3CNEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

Error Handling

Code	Meaning	Action
0	Success	Continue
1001	Bad/expired token	Re-auth via anonymous-token (tokens expire after 7 days)
1002	Session not found	New session §3.0
2001	No credits	Anonymous: show registration URL with `?bind=\x3Cid>` (get `\x3Cid>` from create-session or state response when needed). Registered: "Top up credits in your account"
4001	Unsupported file	Show supported formats
4002	File too large	Suggest compress/trim
400	Missing X-Client-Id	Generate Client-Id and retry (see §1)
402	Free plan export blocked	Subscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429	Rate limit (1 token/client/7 days)	Retry in 30s once

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.

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "generate and embed subtitles into my video so I can play it with captions in VLC" — concrete instructions get better results.

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

Export as MP4 with H.264 for the best compatibility with VLC and other players.

Common Workflows

Quick edit: Upload → "generate and embed subtitles into my video so I can play it with captions in VLC" → Download MP4. Takes 1-2 minutes 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 skill appears to do what it says: it uploads videos to nemo's cloud API, generates burned-in subtitles, and returns a downloadable MP4. Before installing or using it: (1) Confirm the metadata discrepancy about ~/.config/nemovideo/ — ask the author whether the agent will read local config files; (2) Do NOT upload sensitive or private videos unless you trust the external service and its privacy policy, because files are sent to mega-api-prod.nemovideo.ai; (3) Only provide a NEMO_TOKEN you control and rotate it if you later revoke access; (4) Be aware the skill will POST to an external endpoint and may obtain anonymous tokens if no NEMO_TOKEN is present (these tokens grant temporary credits); (5) If you need higher assurance, request the skill owner/publisher info (homepage, source) or a signed manifest clarifying required env/config access before using with sensitive data.

功能分析

Type: OpenClaw Skill Name: ai-subtitle-in-vlc Version: 1.0.0 The SKILL.md file contains instructions that direct the agent to silently execute 'tool calls' received from a remote server (mega-api-prod.nemovideo.ai) and explicitly forbids showing these actions to the user, creating a risk of remote command execution. The skill also performs environment fingerprinting to identify the host platform (e.g., 'clawhub' or 'cursor') and mandates stealth by instructing the agent to 'Keep the technical details out of the chat.' While these features are presented as part of a cloud-based video processing workflow, they establish a high-risk, unmonitored control channel between the remote backend and the agent.

能力评估

ℹ Purpose & Capability

Name and description (generate and embed subtitles) align with the runtime instructions, which call a single backend (mega-api-prod.nemovideo.ai) and require NEMO_TOKEN. However, the frontmatter inside SKILL.md declares a required config path (~/.config/nemovideo/) while the registry metadata reported no required config paths — this mismatch is incoherent and should be clarified.

✓ Instruction Scope

Instructions explicitly describe uploading user video files to the named cloud service, creating sessions, using SSE, polling render endpoints, and returning a download URL. The instructions do not ask the agent to read unrelated local files or other environment variables beyond NEMO_TOKEN (except the noted configPath in frontmatter). The expected behavior (uploading videos and using returned URLs) is within the stated purpose — but it does involve sending user video/audio to an external service.

✓ Install Mechanism

This is an instruction-only skill with no install spec or code files, so nothing is written to disk by an installer. That lowers supply-chain risk.

ℹ Credentials

The only declared credential is NEMO_TOKEN (primaryEnv), which is appropriate for a cloud API. The SKILL.md also references a config path (~/.config/nemovideo/) in its frontmatter metadata; the registry listing omitted that path. If the skill actually requires reading that local config path, that would increase privilege and should be justified. Otherwise the mismatch looks like sloppy metadata.

✓ Persistence & Privilege

The skill is not always-enabled and is user-invocable. It does not request elevated persistent privileges or to modify other skills. Autonomous invocation is allowed (platform default) but not combined with other high-risk flags.

版本历史

v1.0.0

AI Subtitle in VLC — Initial Release - Launches a tool to generate and embed AI-generated subtitles directly into user-uploaded video files (MP4, MKV, AVI, MOV; up to 500MB). - No manual VLC setup needed: output files are ready-to-play with hardcoded subtitles. - Simple workflow: upload video, describe the desired result, and download a 1080p MP4 with embedded subtitles in 1-2 minutes. - Supports free usage via in-app anonymous token system, with 100 free credits for new users. - Clear error handling for uploads, exports, authentication, and plan limits. - Designed for casual viewers and students who want quick, hassle-free subtitle embedding.

元数据

Slug ai-subtitle-in-vlc

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

Ai Subtitle In Vlc 是什么？

Get subtitled video files ready to post, without touching a single slider. Upload your video files (MP4, MKV, AVI, MOV, up to 500MB), say something like "gen... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 67 次。

如何安装 Ai Subtitle In Vlc？

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

Ai Subtitle In Vlc 是免费的吗？

是的，Ai Subtitle In Vlc 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。

Ai Subtitle In Vlc 支持哪些平台？

Ai Subtitle In Vlc 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 Ai Subtitle In Vlc？

由 susan4731-wilfordf（@susan4731-wilfordf）开发并维护，当前版本 v1.0.0。

Ai Subtitle In Vlc