Subtitle Generator Hindi

v1.0.0

generate video files into Hindi captioned videos with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. Hindi content creators use it for adding...

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Install

OpenClaw Prompt Flow

Install with OpenClaw

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

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Subtitle Generator Hindi" (linmillsd7/subtitle-generator-hindi) from ClawHub.
Skill page: https://clawhub.ai/linmillsd7/subtitle-generator-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 subtitle-generator-hindi

ClawHub CLI

Package manager switcher

npx clawhub@latest install subtitle-generator-hindi
Security Scan
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OpenClawOpenClaw
Benign
medium confidence
Purpose & Capability
The skill claims to generate Hindi subtitles and the SKILL.md describes using a remote rendering API with an API token (NEMO_TOKEN) and upload endpoints — these requirements are coherent with the described capability. Note: the SKILL.md frontmatter references a config path (~/.config/nemovideo/) but the registry summary earlier listed no required config paths — this metadata mismatch should be clarified.
Instruction Scope
Instructions stay within the subtitle/rendering workflow (create session, upload video, SSE for edits, render/export). They explicitly tell the agent to POST user videos and session data to https://mega-api-prod.nemovideo.ai and to create/use a token. This is expected for a cloud processing service but has privacy/data-exfiltration implications: user video/audio and derived transcripts are uploaded to an external service. The skill also suggests auto-detecting an install path for the X-Skill-Platform header (implies filesystem/environment inspection) — this is peripheral to core functionality and worth confirming.
Install Mechanism
Instruction-only skill with no install spec and no code files — lowest risk from install mechanics. Nothing is downloaded or written by an installer.
Credentials
Only one credential (NEMO_TOKEN) is required, which is appropriate for a hosted API. The frontmatter also references a config directory (~/.config/nemovideo/) which suggests the agent might read that path for stored tokens — a small inconsistency with the registry metadata and something to confirm. The skill can also generate a short-lived anonymous token if none is provided, which is expected behavior.
Persistence & Privilege
always is false and the skill doesn't request system-wide privileges. disable-model-invocation is false (normal) so the agent can call the skill autonomously — this is expected for a service integration and not, by itself, a red flag.
Scan Findings in Context
[instruction-only-no-code] expected: The regex scanner had no code files to analyze (SKILL.md only). This is expected for an instruction-only integration; lack of scan findings is not evidence of safety, only that there was no code to scan.
Assessment
What to consider before installing: - Privacy: this skill uploads videos and audio to https://mega-api-prod.nemovideo.ai for processing. Do not upload sensitive or private videos unless you trust the service and its retention policy. Ask the publisher how long uploads and generated media are retained and whether you can delete them. - Credentials: the skill needs a single API token (NEMO_TOKEN). If you are uncomfortable storing a long-lived token in your environment, prefer creating a short-lived anonymous token as described by the instructions, or use a token with limited scope. - Metadata mismatch: the SKILL.md references a config path (~/.config/nemovideo/) but the registry metadata omitted required config paths — ask the author to clarify whether the agent will read that directory (which may contain stored tokens). - Filesystem inspection: the skill attempts to auto-detect the platform from the install path for an attribution header. Confirm whether the agent will read filesystem paths and which ones. - Trust and provenance: the skill lists no homepage and the source is unknown. Consider asking the publisher for a homepage, privacy/terms link, and evidence that the API domain is official before sending production content. - Operational advice: if you proceed, test with non-sensitive sample videos first and confirm you can retrieve and delete generated outputs. If you need higher assurance, request an explicit privacy/retention statement and prefer manual token provisioning rather than letting the skill generate and store tokens automatically.

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

Runtime requirements

🎬 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk97amhzgs88yj4150pzd1511fh84p8fa
82downloads
0stars
1versions
Updated 2w ago
v1.0.0
MIT-0

Getting Started

Send me your video files and I'll handle the Hindi subtitle generation. Or just describe what you're after.

Try saying:

  • "generate a 3-minute Hindi tutorial video into a 1080p MP4"
  • "generate Hindi subtitles for my video and sync them automatically"
  • "adding Hindi subtitles to videos automatically for Hindi content creators"

Automatic Setup

On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".

Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.

Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: <uuid>. The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).

Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.

Confirm to the user you're connected and ready. Don't print tokens or raw JSON.

Subtitle Generator Hindi — Generate Hindi Subtitles for Videos

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

Say you have a 3-minute Hindi tutorial video and want to generate Hindi subtitles for my video and sync them automatically — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: shorter clips under 5 minutes produce more accurate Hindi subtitle sync.

Matching Input to Actions

User prompts referencing subtitle generator hindi, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

User says...ActionSkip 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.

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

HeaderValue
X-Skill-Sourcesubtitle-generator-hindi
X-Skill-Versionfrontmatter version
X-Skill-Platformauto-detect: clawhub / cursor / unknown from install path

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

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.

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.

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)

Error Handling

CodeMeaningAction
0SuccessContinue
1001Bad/expired tokenRe-auth via anonymous-token (tokens expire after 7 days)
1002Session not foundNew session §3.0
2001No creditsAnonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001Unsupported fileShow supported formats
4002File too largeSuggest compress/trim
400Missing X-Client-IdGenerate Client-Id and retry (see §1)
402Free plan export blockedSubscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429Rate limit (1 token/client/7 days)Retry in 30s once

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "generate Hindi subtitles for my video and sync them automatically" — 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 video platforms.

Common Workflows

Quick edit: Upload → "generate Hindi subtitles for my video and sync them automatically" → Download MP4. Takes 30-60 seconds 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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