Video Edit Free

Turn a 2-minute unedited phone recording into 1080p edited video clips just by typing what you need. Whether it's editing raw footage into a finished video w...

Security Scan

The skill's requirements and runtime instructions mostly match a remote video-editing service, but there are small inconsistencies (metadata vs. registry) and privacy risks from uploading user videos and trusting an external token-based API that you should understand before installing.

Purpose & Capability

The skill is a remote video editing frontend and requests a single API token (NEMO_TOKEN), which fits the stated purpose. However, the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) and asks the agent to auto-detect an install path for X-Skill-Platform — registry metadata shown earlier listed no config paths. That mismatch is an internal inconsistency and could imply additional filesystem access that isn't otherwise documented.

Instruction Scope

SKILL.md instructs the agent to obtain or reuse a NEMO_TOKEN, create sessions, upload potentially large user video/audio files to https://mega-api-prod.nemovideo.ai, stream SSE events, and poll render status. Those actions are coherent with video-editing, but they involve transmitting user media (potentially sensitive) to a third party. The spec also asks the agent to 'auto-detect' a platform value from an install path, which may require reading local environment/paths — this is not fully explained.

Install Mechanism

Instruction-only skill (no install stanza, no downloaded code). Lowest installation risk: nothing is written to disk by an installer. All runtime behavior is via HTTP API calls described in SKILL.md.

Credentials

Only one environment variable is declared (NEMO_TOKEN / primaryEnv), which is proportionate for a remote API. The skill also specifies behavior to generate an anonymous token if none is present. No unrelated credentials are requested.

Persistence & Privilege

The skill does not request always: true and does not indicate it will modify other skills or system-wide configs. It does instruct saving session_id and token state for the session lifecycle, which is reasonable for its function.

What to consider before installing

This skill appears to implement a remote video-editing service and will upload whatever you give it to mega-api-prod.nemovideo.ai using a NEMO_TOKEN. Before installing or using it: 1) Confirm the service domain and privacy/TOS — uploading sensitive or private video/audio will send that data to an external provider. 2) Verify where the skill came from (owner ID is not a known vendor); unknown sources increase risk. 3) Note the small metadata inconsistency (SKILL.md references a config path and auto-detecting install path) — ask the author whether the agent will read any local config or filesystem paths. 4) Prefer using a temporary anonymous token rather than a long-lived credential, and do not reuse high-privilege tokens. 5) If you need stronger assurances, request a signed provenance or an official endpoint from the vendor and ask for clarity about what, if anything, the skill will read from your local filesystem.

Getting Started

Ready when you are. Drop your raw video clips here or describe what you want to make.

Try saying:

• "edit a 2-minute unedited phone recording into a 1080p MP4"
• "trim the pauses, add transitions, and export a clean final cut"
• "editing raw footage into a finished video without paid software for casual creators and students"

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.

Video Edit Free — Edit and Export Videos Free

Send me your raw video clips and describe the result you want. The AI automated editing runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 2-minute unedited phone recording, type "trim the pauses, add transitions, and export a clean final cut", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter clips under 60 seconds process faster and give cleaner AI results.

Matching Input to Actions

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

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.

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 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)

Common Workflows

Quick edit: Upload → "trim the pauses, add transitions, and export a clean final cut" → 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "trim the pauses, add transitions, and export a clean final cut" — 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 platforms and devices.