Subtitle Generator Bangla

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

Security Scan

The skill's stated purpose (Bangla subtitle generation) matches most of its instructions and the single required credential (NEMO_TOKEN), but the runtime instructions ask the agent to read local install/config paths and allow uploading by local filesystem path — behaviors that are not strictly necessary and increase risk.

Purpose & Capability

Name/description, API endpoints, and NEMO_TOKEN requirement align with a cloud subtitle-generation service. Minor incoherence: the registry metadata reported no required config paths, but SKILL.md frontmatter lists a config path (~/.config/nemovideo/), implying the skill may try to read local config files.

Instruction Scope

Instructions direct the agent to upload files via multipart using local file paths (e.g. -F "files=@/path") and to detect install path prefixes (~/.clawhub/, ~/.cursor/skills/) to set X-Skill-Platform. Allowing path-based uploads and filesystem probing gives the agent scope to read arbitrary local files beyond user-dropped uploads — this is not necessary for the stated purpose and broadens data access.

Install Mechanism

No install spec or code files are present (instruction-only), so nothing will be written to disk by an installer. This is the lowest-risk install model.

Credentials

Only one credential is required (NEMO_TOKEN), which is proportionate to a cloud API. However, the frontmatter's configPaths and the skill's behavior for platform detection imply additional local config or path reading that wasn't declared in the registry metadata — an inconsistency to clarify.

Persistence & Privilege

always:false and no special privileges requested. The skill asks to save session_id and ephemeral tokens for its workflow, which is reasonable for a remote-rendering service and does not request permanent platform-wide privileges.

What to consider before installing

This skill mostly behaves like a cloud subtitle service, but it instructs the agent to probe install/config paths and to upload files by local filesystem path — actions that can expose more local data than necessary. Before installing or using it: (1) Prefer using the anonymous token flow (ephemeral) rather than placing a long-lived NEMO_TOKEN in your environment. (2) Only send files via the chat upload UI; do not allow the agent to reference arbitrary local filesystem paths. (3) Ask the publisher to clarify why the skill needs to detect ~/.clawhub/ or ~/.cursor/skills/ and whether it will read ~/.config/nemovideo/; if unnecessary, request removal of filesystem probing. (4) Verify the API domain (mega-api-prod.nemovideo.ai) and its privacy/retention policy for uploaded media. If you cannot confirm these, treat the skill as higher-risk and avoid using it with sensitive or private files.

Getting Started

Share your video files and I'll get started on Bangla subtitle generation. Or just tell me what you're thinking.

Try saying:

• "generate my video files"
• "export 1080p MP4"
• "generate subtitles in Bangla and sync"

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 Bangla — Generate Bangla Subtitles for Videos

Drop your video files in the chat and tell me what you need. I'll handle the Bangla subtitle generation on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 3-minute Bengali YouTube video, ask for generate subtitles in Bangla and sync them to my video, 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 5 minutes produce more accurate Bangla subtitle sync.

Matching Input to Actions

User prompts referencing subtitle generator bangla, 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is subtitle-generator-bangla, 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).

All requests must include: Authorization: Bearer <NEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 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 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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "generate subtitles in Bangla and sync them to my video" — 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 Bengali social platforms.

Common Workflows

Quick edit: Upload → "generate subtitles in Bangla and sync them to my video" → 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.