Hindi Video Editing With

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...

Security Scan

The skill is broadly coherent for a cloud-based Hindi video editing service and only needs a single service token, but there are small inconsistencies and a couple of scope/privacy signals you should review before installing.

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.

What to consider before installing

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.

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. Session — POST /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. Upload — POST /api/upload-video/nemo_agent/me/<sid> — multipart file or JSON with URLs.
4. Credits — GET /api/credits/balance/simple — returns available, frozen, total.
5. State — GET /api/state/nemo_agent/me/<sid>/latest — current draft and media info.
6. Export — POST /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.

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 <NEMO_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=<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

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.