Ai Video Editor Hindi

Get edited Hindi videos ready to post, without touching a single slider. Upload your raw video footage (MP4, MOV, AVI, WebM, up to 500MB), say something like...

Security Scan

The skill's described editing behavior matches its instructions, but there are inconsistencies (declared required token vs. anonymous token flow, unused configPath metadata) and the runtime instructions will upload user videos and fetch tokens from an external API — you should review data-sharing and token practices before installing.

Purpose & Capability

The name/description (AI Hindi video editing) aligns with the instructions to upload video files and call a cloud render API. However the metadata declares NEMO_TOKEN as a required primary credential while the SKILL.md also describes automatically obtaining an anonymous token if none is present — that's inconsistent. Metadata also lists a config path (~/.config/nemovideo/) that the runtime text does not clearly use.

Instruction Scope

Runtime instructions will upload user video files to https://mega-api-prod.nemovideo.ai, create and store session tokens, and read environment and local install-path information to construct attribution headers. Uploading user files and making network calls is expected for this skill, but the instructions also direct the agent to detect install paths and derive headers from local paths (e.g., ~/.clawhub/, ~/.cursor/skills/) — that requires filesystem checks outside just handling the provided video and is broader than strictly necessary for editing.

Install Mechanism

No install spec or code is present (instruction-only), so nothing is written to disk by an installer. This lowers supply-chain risk.

Credentials

The skill declares a single required env var (NEMO_TOKEN) which is appropriate for a service-backed editor, but the SKILL.md instructs the agent to obtain an anonymous token automatically if NEMO_TOKEN is missing — making the declaration misleading. The metadata also lists a config path that is not otherwise justified. Requiring or using a long-lived token would grant the backend access to all uploads/sessions; anonymous tokens are time-limited but still transmit user content to the external service.

Persistence & Privilege

The skill is not marked always:true and does not request persistent system privileges. It can invoke autonomously (platform default), which increases blast radius if combined with other red flags but is by itself normal.

What to consider before installing

This skill will upload any videos you provide to an external service (mega-api-prod.nemovideo.ai) and will create or use a NEMO_TOKEN to perform edits. Before installing or using it: 1) Do not upload sensitive/personal videos unless you trust the service and have reviewed its privacy/TOS. 2) Ask the author or vendor for a privacy policy and retention rules (how long uploads and generated tokens are kept). 3) Be aware the skill can auto-request an anonymous token if NEMO_TOKEN isn't set — if you prefer control, set and manage your own token rather than relying on anonymous issuance. 4) Note the skill inspects local installation paths to build headers; if you’re uncomfortable with any local filesystem checks, avoid installing. If you want this skill but need stronger assurances, request the service's security/privacy documentation and consider isolating uploads (e.g., test with non-sensitive clips first).

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 pauses, and"

Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:

• Generate a UUID as client identifier
• POST https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
• Extract data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

AI Video Editor Hindi — Edit Hindi Videos with AI

Drop your raw video footage in the chat and tell me what you need. I'll handle the AI Hindi video editing on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 2-minute Hindi vlog recorded on a smartphone, ask for add Hindi subtitles, trim pauses, and add background music, and about 1-2 minutes later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — uploading clips under 5 minutes gives faster and more accurate Hindi subtitle generation.

Matching Input to Actions

User prompts referencing ai video editor hindi, 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.

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

Headers are derived from this file's YAML frontmatter. X-Skill-Source is ai-video-editor-hindi, 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).

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

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

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

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

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

Session state: GET /api/state/nemo_agent/me/<sid>/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_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/<id> 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.

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

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.

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)

Common Workflows

Quick edit: Upload → "add Hindi subtitles, trim pauses, 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 pauses, 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.