Ai Subtitle Remover

remove video with subtitles into clean subtitle-free video with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators and video edit...

Security Scan

The skill's requests and runtime instructions are coherent with its stated purpose: it calls a cloud video-processing API and requires a single service token (NEMO_TOKEN); there are no unrelated credentials, installs, or odd binaries requested.

Purpose & Capability

Name/description (remove burned-in subtitles) match the runtime instructions: the SKILL.md documents calls to a nemo video-processing API, upload endpoints, render/export endpoints, and a required NEMO_TOKEN. Asking for a service token and using a remote render API is proportionate to the stated capability.

Instruction Scope

Most instructions stay within the subtitle-removal workflow (auth, create session, upload, SSE, export). Two items to note: (1) the skill auto-generates an anonymous token by POSTing to an external endpoint if NEMO_TOKEN is not set — this will create a short-lived token and cause the agent to interact with the remote service without an explicit pre-provided credential; (2) the runtime asks the agent to detect install path (e.g., ~/.clawhub/ or ~/.cursor/skills/) to set an attribution header, implying the agent may read its own filesystem paths. Neither is obviously malicious but they are wider in scope than purely uploading a provided video.

Install Mechanism

Instruction-only skill with no install steps or downloads. No code files to be written or executed on install, which minimizes on-disk risk.

Credentials

The only required environment credential is NEMO_TOKEN (declared as primary). That aligns with the need to call the external nemo API. No unrelated secrets or large sets of env vars are requested.

Persistence & Privilege

always is false and the skill does not request elevated platform privileges. It suggests storing a session_id and token for subsequent requests (expected for a session-based API) but does not instruct modifying other skills or system-wide configs.

Assessment

This skill uploads user videos to an external service (mega-api-prod.nemovideo.ai) and will either use a provided NEMO_TOKEN or automatically request an anonymous token on your behalf. Before installing, consider: (1) Privacy — any video you upload will be sent to their cloud GPUs; avoid uploading sensitive or copyrighted material unless you trust their terms and retention policy. (2) Token handling — the skill stores a session token and asks you not to display raw tokens; if you want control, set NEMO_TOKEN yourself instead of relying on anonymous token creation. (3) Attribution headers and small filesystem checks — the agent may inspect its install path to set X-Skill-Platform; if you’re uncomfortable with that, limit where you run the skill or review runtime logs. The skill appears internally consistent, but verify you trust the remote service and its privacy/retention practices before sending private content.

Getting Started

Send me your video with subtitles and I'll handle the AI subtitle removal. Or just describe what you're after.

Try saying:

• "remove a 2-minute YouTube video with burned-in subtitles into a 1080p MP4"
• "remove the hardcoded subtitles from this video"
• "removing hardcoded subtitles from videos for content creators and video editors"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer <token>, Content-Type: application/json, and body {"task_name":"project","language":"<detected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

AI Subtitle Remover — Remove Subtitles from Videos

Drop your video with subtitles in the chat and tell me what you need. I'll handle the AI subtitle removal on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 2-minute YouTube video with burned-in subtitles, ask for remove the hardcoded subtitles from this video, and about 30-90 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter clips with high-contrast backgrounds yield the cleanest subtitle removal.

Matching Input to Actions

User prompts referencing ai subtitle remover, 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.

Skill attribution — read from this file's YAML frontmatter at runtime:

• X-Skill-Source: ai-subtitle-remover
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)

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.

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

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)

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 → "remove the hardcoded subtitles from this video" → Download MP4. Takes 30-90 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "remove the hardcoded subtitles from this 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.