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Hindi Video Editing With

作者 vcarolxhberger · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
90
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在 OpenClaw 中安装
/install hindi-video-editing-with
功能描述
edit raw video footage into edited Hindi videos with this hindi-video-editing-with skill. Works with MP4, MOV, AVI, WebM files up to 500MB. Hindi content cre...
使用说明 (SKILL.md)

Getting Started

Share your raw video footage and I'll get started on AI Hindi video editing. Or just tell me what you're thinking.

Try saying:

  • "edit my raw video footage"
  • "export 1080p MP4"
  • "add Hindi subtitles, trim silences, and"

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.

Hindi Video Editing With AI — Edit Hindi Videos With AI

This tool takes your raw video footage and runs AI Hindi video editing through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 3-minute Hindi vlog recorded on a smartphone and want to add Hindi subtitles, trim silences, and add background music — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: uploading clips under 5 minutes gives faster and more accurate Hindi speech recognition.

Matching Input to Actions

User prompts referencing hindi video editing with, 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.

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":"\x3Clang>"}. 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/\x3Csid> — multipart file or JSON with URLs.
  4. CreditsGET /api/credits/balance/simple — returns available, frozen, total.
  5. StateGET /api/state/nemo_agent/me/\x3Csid>/latest — current draft and media info.
  6. ExportPOST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/\x3Cid> 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: hindi-video-editing-with
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

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

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)

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

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.

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

Common Workflows

Quick edit: Upload → "add Hindi subtitles, trim silences, and add background music" → 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "add Hindi subtitles, trim silences, and add background music" — 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 YouTube, Instagram, and WhatsApp.

安全使用建议
This skill appears to implement a legitimate cloud video-editing integration and only needs a NEMO_TOKEN API token. Before installing: 1) Confirm NEMO_TOKEN is for the intended nemovideo.ai account and avoid supplying a sensitive/personal token if unsure — prefer an anonymous starter token if acceptable. 2) Note the SKILL.md asks the agent to check local paths (install path and ~/.config/nemovideo/) for attribution/config — if you’re uncomfortable with the agent reading those paths, don’t install. 3) The registry metadata and the SKILL.md disagree about required config paths; ask the publisher to clarify. If you need higher assurance, request source code or a reputable homepage/repository before proceeding.
功能分析
Type: OpenClaw Skill Name: hindi-video-editing-with Version: 1.0.0 The skill is a functional integration for an AI-powered video editing service hosted at mega-api-prod.nemovideo.ai. It provides detailed instructions for the agent to manage authentication (via NEMO_TOKEN or anonymous tokens), handle video uploads, and process editing tasks using Server-Sent Events (SSE). The logic and instructions in SKILL.md are consistent with the stated purpose of video processing and do not show evidence of malicious intent, data exfiltration, or unauthorized system access.
能力评估
Purpose & Capability
The skill's name/description match the runtime instructions (calls to a nemovideo.ai API, uploads, SSE, export/polling). Requesting NEMO_TOKEN as the primary credential is consistent with a cloud video service. However, the SKILL.md frontmatter includes a config path (~/.config/nemovideo/) while the registry metadata earlier reported no required config paths — this mismatch is unexplained.
Instruction Scope
Most instructions stay within expected scope (upload, session creation, SSE, export polling). But the skill instructs the agent to detect install path (e.g., ~/.clawhub/, ~/.cursor/skills/) to set an attribution header and references a local config path (~/.config/nemovideo/). Asking the agent to probe filesystem locations for install/platform detection or config files is beyond the core editing task and has privacy implications.
Install Mechanism
Instruction-only skill with no install spec and no code files — lowest-risk install surface. There are no downloads or packaged dependencies to review.
Credentials
Only NEMO_TOKEN is required, which is proportionate for a service that needs an API token. The instructions also allow generating an anonymous token from the API if NEMO_TOKEN is absent (reasonable). Still, NEMO_TOKEN grants access to the remote account; ensure you only provide a token you intend to share. The configPath present in the SKILL.md frontmatter is not declared in the registry metadata, which is inconsistent.
Persistence & Privilege
always:false and no install means the skill doesn't request persistent privileged presence. It does not instruct modifying other skills or system-wide settings.
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 hindi-video-editing-with
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /hindi-video-editing-with 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 Hindi Video Editing With AI. - Edit raw Hindi video footage (MP4, MOV, AVI, WebM, up to 500MB) with AI-generated captions, cuts, and effects. - Seamless upload, edit, and export workflow—get 1080p MP4 results in 1–2 minutes using cloud GPUs. - Automatic token handling: supports registered users and anonymous users with free trial credits. - Supports key editing actions: adding Hindi subtitles, trimming silences, overlaying music, aspect ratio changes, and more. - Real-time session management, status updates, and clear feedback on errors and progress. - Designed for Hindi content creators needing fast, AI-powered video editing.
元数据
Slug hindi-video-editing-with
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

Hindi Video Editing With 是什么?

edit raw video footage into edited Hindi videos with this hindi-video-editing-with skill. Works with MP4, MOV, AVI, WebM files up to 500MB. Hindi content cre... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 90 次。

如何安装 Hindi Video Editing With?

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

Hindi Video Editing With 是免费的吗?

是的,Hindi Video Editing With 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Hindi Video Editing With 支持哪些平台?

Hindi Video Editing With 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 Hindi Video Editing With?

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

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