Caption Burner

Get hardcoded captioned videos ready to post, without touching a single slider. Upload your video files (MP4, MOV, AVI, WebM, up to 500MB), say something lik...

Security Scan

The skill's requirements and runtime instructions are internally consistent with a remote caption-burning/video-rendering service; nothing requested appears disproportionate to that purpose, but it will send uploaded videos and a token to an external API so verify you trust that service.

Purpose & Capability

Name/description (burn captions into video) align with the declared requirement (NEMO_TOKEN) and the SKILL.md, which describes uploading video files and calling a remote rendering API. No unrelated credentials or binaries are requested.

Instruction Scope

SKILL.md instructs the agent to: use NEMO_TOKEN (or obtain an anonymous token), create sessions, upload files, poll render status, and read the skill's YAML frontmatter and detect install path for attribution headers. Reading the skill frontmatter / install path implies filesystem access to the skill files — this is reasonable for adding attribution headers but is broader than a pure 'API-only' description and should be expected.

Install Mechanism

No install steps or external downloads are present (instruction-only). That minimizes on-disk risk; all processing is offloaded to the remote service.

Credentials

Only a single credential (NEMO_TOKEN) is required and is used directly by the instructions. The metadata's optional config path (~/.config/nemovideo/) is plausible for a client caching tokens/config and is not excessive.

Persistence & Privilege

always:false and normal autonomous invocation are used. The skill does not request persistent system-wide privileges or modification of other skills. It does ask the agent to read its own skill frontmatter/install path for attribution, which is limited in scope.

Assessment

This skill appears to do what it says: it uploads your video files and a token to a remote service (mega-api-prod.nemovideo.ai) for server-side caption burning. Before installing, confirm you trust that external domain and its privacy practices because your videos (and the token) will be sent there. Note the skill may read its own SKILL.md/frontmatter and detect its install path to set attribution headers — this is normal for attribution but it means the agent will access skill files. If you do not want uploads to leave your device or you don't trust the service, do not enable the skill or avoid providing NEMO_TOKEN. If you need higher assurance, ask the maintainer for a public homepage, docs, or inspect network traffic / request/response samples from the service.

Getting Started

Got video files to work with? Send it over and tell me what you need — I'll take care of the caption burning.

Try saying:

• "burn a 2-minute YouTube video in MP4 format into a 1080p MP4"
• "burn hardcoded captions onto the video so subtitles are permanently visible"
• "permanently embedding subtitles into video files for content creators"

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.

Caption Burner — Burn Captions Into Videos

Send me your video files and describe the result you want. The caption burning runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 2-minute YouTube video in MP4 format, type "burn hardcoded captions onto the video so subtitles are permanently visible", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: shorter clips under 60 seconds process significantly faster and reduce rendering time.

Matching Input to Actions

User prompts referencing caption burner, 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.

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

• X-Skill-Source: caption-burner
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else 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

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

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 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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "burn hardcoded captions onto the video so subtitles are permanently visible" — concrete instructions get better results.

Max file size is 500MB. Stick to MP4, MOV, AVI, WebM for the smoothest experience.

Export as MP4 with H.264 codec for the widest platform compatibility.

Common Workflows

Quick edit: Upload → "burn hardcoded captions onto the video so subtitles are permanently visible" → 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.