Free Video To

Get converted video files ready to post, without touching a single slider. Upload your video files (MP4, MOV, AVI, WebM, up to 500MB), say something like "co...

Security Scan

The skill's instructions line up with a cloud video-conversion service, but there are small metadata/instruction mismatches and privacy/network implications you should understand before installing.

Purpose & Capability

The name/description (cloud video conversion) matches the runtime instructions (upload files, create session, render on remote GPUs). Requesting a NEMO_TOKEN is coherent. However, the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) that the registry metadata did not — this mismatch is unexplained and worth clarifying.

Instruction Scope

SKILL.md instructs the agent to upload user video files and metadata to mega-api-prod.nemovideo.ai, create sessions, stream SSE, and poll for render results — all expected for the stated purpose. The skill will obtain or use a bearer token (NEMO_TOKEN) and may call an anonymous-token endpoint if none is present. It does not instruct reading unrelated local files or broad environment scanning, but it does require uploading potentially sensitive video content to a third-party service (privacy/retention risk).

Install Mechanism

Instruction-only skill with no install spec and no code files, so nothing is written to disk by an installer. This is the lowest install risk.

Credentials

Only one environment variable (NEMO_TOKEN) is declared as required, which is proportional for an API-based conversion service. Two minor issues: (1) SKILL.md will auto-request an anonymous token if NEMO_TOKEN is not set (so the skill doesn't strictly need a pre-provided token), and (2) SKILL.md frontmatter references a config path that the registry metadata does not list. Both are inconsistencies you should confirm with the author. Consider not putting sensitive global secrets in NEMO_TOKEN unless you trust the service.

Persistence & Privilege

always:false (default) and no instructions to modify other skills or system-wide settings. The agent can invoke the skill autonomously (normal default) but the skill does not request elevated or persistent local privileges.

What to consider before installing

This skill appears to do what it says (upload your video and get back a converted file) but you should be cautious before installing/use: 1) Privacy: the skill uploads your videos to mega-api-prod.nemovideo.ai — confirm the service's privacy/retention policy before sending sensitive content. 2) Token behavior: the skill will use NEMO_TOKEN if present, or automatically request an anonymous token and use that — decide whether you want to place a token in your environment or let it create an anonymous token. 3) Metadata mismatch: SKILL.md mentions a config path (~/.config/nemovideo/) that the registry metadata omitted — ask the publisher why. 4) Trust/source: source/homepage is unknown; verify the publisher identity or prefer a skill with a known homepage/repository. 5) If you proceed, prefer using a dedicated (limited) account or ephemeral environment and monitor network activity if you have sensitive data. If you need higher assurance, ask the developer for a privacy statement, token storage behavior (is the token persisted locally?), and the canonical service domain/ownership.

Getting Started

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

Try saying:

• "convert my video files"
• "export 1080p MP4"
• "convert this video to a short"

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.

Free Video To — Convert and Export Video Files

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

A quick example: upload a 2-minute MP4 tutorial recording, type "convert this video to a short clip with captions and music", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: shorter source clips under 3 minutes convert significantly faster.

Matching Input to Actions

User prompts referencing free video to, 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	free-video-to
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-detect: clawhub / cursor / unknown from install path

Include Authorization: Bearer <NEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

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.

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "convert this video to a short clip with captions and music" — 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 all platforms.

Common Workflows

Quick edit: Upload → "convert this video to a short clip with captions and music" → 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.