Video To Audio

Skip the learning curve of professional editing software. Describe what you want — extract the audio track from my video as an MP3 file — and get extracted a...

Security Scan

The skill's requirements and runtime instructions are internally consistent with a cloud-based video→audio extraction service, with only minor metadata/information discrepancies and the usual privacy considerations of sending files to a remote backend.

Purpose & Capability

The skill claims to upload video files and run a cloud render pipeline; requesting an API token (NEMO_TOKEN) and calling the listed nemo API endpoints is coherent with that purpose. The attribution headers and session flow described match a remote-processing design.

Instruction Scope

Instructions explicitly tell the agent to upload user media, create sessions, read/maintain a session_id, and stream SSE responses — all expected for a cloud render workflow. They also instruct generating an anonymous token when NEMO_TOKEN is absent and to auto-detect an install platform from an install path; the latter implies the agent may inspect its environment/install path. This is expected for header population but is broader than a purely local-only tool and should be understood before use.

Install Mechanism

No install spec or downloads are present (instruction-only). Nothing is written to disk by an installer in the skill bundle itself, which is the lowest install risk.

Credentials

The skill requests a single credential (NEMO_TOKEN) which is proportional to a remote processing service. Two small discrepancies: (1) the registry metadata you provided lists no required config paths, but the SKILL.md frontmatter's metadata lists a config path (~/.config/nemovideo/), and (2) the SKILL.md also describes generating an anonymous token when NEMO_TOKEN is absent — meaning the skill can obtain a transient token itself. Both are explainable but worth noting before trusting the skill.

Persistence & Privilege

The skill is not always-on and does not request elevated platform privileges. It uses short-lived session tokens for cloud jobs; nothing in the skill attempts to modify other skills or system-wide settings.

Assessment

This skill uploads your video files to an external backend (mega-api-prod.nemovideo.ai) for processing and requires a NEMO_TOKEN (or will request an anonymous token on first use). Before installing: (1) confirm you trust the remote service and are comfortable with your media being uploaded to that domain; (2) verify the token scope and retention policy (anonymous tokens are described as 7-day, 100 free credits); (3) note the small metadata mismatch (SKILL.md lists a config path ~/.config/nemovideo/ while registry metadata did not) — ask the author which is authoritative; (4) if you need stronger privacy, avoid using the skill or only upload non-sensitive clips; (5) prefer skills with a known homepage or owner for accountability. If you want higher assurance, ask the publisher for a privacy/security statement and a canonical endpoint and compare that to the endpoints in SKILL.md.

Getting Started

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

Try saying:

• "extract my video files"
• "export 1080p MP4"
• "extract the audio track from my"

Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:

• Generate a UUID as client identifier
• POST https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
• Extract data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

Video to Audio — Extract Audio from Video Files

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

A quick example: upload a 3-minute MP4 interview recording, type "extract the audio track from my video as an MP3 file", and you'll get a 1080p MP4 back in roughly 20-40 seconds. All rendering happens server-side.

Worth noting: shorter clips process faster and produce cleaner audio output.

Matching Input to Actions

User prompts referencing video to audio, 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.

Base URL: https://mega-api-prod.nemovideo.ai

Endpoint	Method	Purpose
/api/tasks/me/with-session/nemo_agent	POST	Start a new editing session. Body: {"task_name":"project","language":"<lang>"}. Returns session_id.
/run_sse	POST	Send a user message. Body includes app_name, session_id, new_message. Stream response with Accept: text/event-stream. Timeout: 15 min.
/api/upload-video/nemo_agent/me/<sid>	POST	Upload a file (multipart) or URL.
/api/credits/balance/simple	GET	Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/<sid>/latest	GET	Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda	POST	Start export. Body: {"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Poll status every 30s.

Accepted file types: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

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

Header	Value
X-Skill-Source	video-to-audio
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-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.

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

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 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 "extract the audio track from my video as an MP3 file" — concrete instructions get better results.

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

MP4 source files give the most reliable audio extraction results.

Common Workflows

Quick edit: Upload → "extract the audio track from my video as an MP3 file" → Download MP4. Takes 20-40 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.