Editor In Hindi

v1.0.0

Turn a 2-minute vlog recorded on a smartphone into 1080p Hindi-captioned videos just by typing what you need. Whether it's editing videos with Hindi text, ca...

⭐ 0· 58·0 current·0 all-time

by@linmillsd7

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for linmillsd7/editor-in-hindi.

Previewing Install & Setup.

Prompt PreviewInstall & Setup

Install the skill "Editor In Hindi" (linmillsd7/editor-in-hindi) from ClawHub.
Skill page: https://clawhub.ai/linmillsd7/editor-in-hindi
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Required env vars: NEMO_TOKEN
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install editor-in-hindi

ClawHub CLI

Package manager switcher

npx clawhub@latest install editor-in-hindi

Security Scan

VirusTotal

Suspicious

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OpenClaw

Benign

high confidence

✓

Purpose & Capability

The name/description (Hindi-captioned video editing) matches the declared primary env var NEMO_TOKEN and the SKILL.md, which details REST calls to a Nemovideo backend. Declared config path (~/.config/nemovideo/) and session-based workflow are consistent with a cloud-render service.

ℹ

Instruction Scope

Instructions stay within video-editing scope (create session, upload video, render/export). They include an anonymous-token fallback flow if NEMO_TOKEN is absent and require sending uploaded files to an external API, which has privacy implications. The doc also says X-Skill-Platform is detected from install paths (e.g., ~/.clawhub/), implying the agent might check filesystem paths to derive a header — this is not explicit about what paths get read, so it's a small scope-related note.

✓

Install Mechanism

Instruction-only skill with no install spec or remote downloads. Nothing is written to disk by an installer; lowest install risk.

✓

Credentials

Only a single credential (NEMO_TOKEN) is required and clearly maps to the backend API. The skill documents creating an anonymous token if no env var is present, which reduces need for extra secrets. Declared config path is specific to the service and proportionate.

✓

Persistence & Privilege

always is false and there is no request for permanent elevated privileges or modifications to other skills or system-wide settings. Autonomous invocation is allowed (platform default) but not coupled with excessive access.

Assessment

This skill appears to do what it says: it will upload your raw videos to mega-api-prod.nemovideo.ai for cloud rendering and use NEMO_TOKEN (or obtain an anonymous token) to run jobs. Before installing, consider: (1) privacy — your videos are sent to an external service, so avoid sensitive content; (2) provenance — the skill's source/homepage is unknown, so verify you trust the Nemovideo service before sharing data or a long-lived token; (3) token handling — if you provide a long-lived NEMO_TOKEN, treat it like a credential (rotate/revoke if needed); and (4) filesystem checks — the skill may attempt to derive a platform header from common install paths, so if you want to be strict, run it in an environment without sensitive config files. If you need more assurance, ask the publisher for a homepage or audit logs showing where uploads are stored and how long they are retained.

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

🎬 Clawdis

EnvNEMO_TOKEN

Primary envNEMO_TOKEN

latestvk9763swfxg3dez4r8qy0c7g72s851fhj

58downloads

0stars

1versions

Updated 1w ago

v1.0.0

MIT-0

Getting Started

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

Try saying:

"edit my raw video footage"
"export 1080p MP4"
"edit this video and add Hindi"

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.

Editor in Hindi — Edit Videos with Hindi Captions

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

Here's a typical use: you send a a 2-minute vlog recorded on a smartphone, ask for edit this video and add Hindi subtitles and captions, 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 — shorter clips under 3 minutes process significantly faster.

Matching Input to Actions

User prompts referencing editor in 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 editor-in-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 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=<id>` (get `<id>` 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

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

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.

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 "edit this video and add Hindi subtitles and captions" — 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 Hindi streaming platforms.

Common Workflows

Quick edit: Upload → "edit this video and add Hindi subtitles and captions" → 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.

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