Editor On Android

Get edited MP4 clips ready to post, without touching a single slider. Upload your video clips (MP4, MOV, AVI, WebM, up to 500MB), say something like "trim th...

Security Scan

The skill's requests and runtime instructions are generally consistent with a remote video-editing service, but there are a few small mismatches and privacy considerations you should review before use.

Purpose & Capability

The skill declares a remote video-editing purpose and its instructions only describe API calls for uploading media, queuing render jobs, streaming events, and downloading results. Requesting an API token (NEMO_TOKEN) and sending files to the described endpoints is consistent with a cloud render pipeline.

Instruction Scope

SKILL.md gives detailed step-by-step API flows (auth, session creation, SSE, upload, render) and instructs the agent to read install paths to set an attribution header. That filesystem check is minor but out-of-band relative to pure editing. The doc also instructs the agent to save session_id and include attribution headers on every request — all coherent for the stated service, but the agent will transmit user-uploaded video/audio to the remote domain, which is a privacy implication.

Install Mechanism

This is an instruction-only skill with no install spec, no downloaded code, and no binaries required. That minimizes local install risk.

Credentials

The only required credential is NEMO_TOKEN (declared as primaryEnv), which fits the API usage. However, the SKILL.md provides an anonymous-token flow if NEMO_TOKEN is not present, so requiring the env var is inconsistent (it's optional in practice). The frontmatter also lists a config path (~/.config/nemovideo/) but the registry metadata reported no required config paths — a small metadata mismatch to be aware of.

Persistence & Privilege

The skill is not always-enabled and does not request elevated platform privileges. It instructs saving only per-session session_id (service-side) and uses bearer auth; there is no instruction to modify other skills or global agent config.

Assessment

This skill appears to do what it says: it uploads media to a remote GPU rendering service and returns edited video. Before installing or using it, consider the following: (1) Privacy — your videos (potentially sensitive) will be transmitted to https://mega-api-prod.nemovideo.ai; test with non-sensitive clips first and confirm the service's privacy/retention policy. (2) Credentials — you can set NEMO_TOKEN for a registered account or the skill can request an anonymous token itself; prefer ephemeral/anonymous tokens if you don't need a persistent account. Do not store high-privilege secrets in NEMO_TOKEN. (3) Metadata mismatch — the skill's frontmatter mentions a config path (~/.config/nemovideo/) and the registry metadata omitted it; this is a small inconsistency but means the skill may probe an expected config location to determine platform attribution. (4) Network transparency — the skill will include Authorization and attribution headers on every request; ensure you are comfortable with that. If you need higher assurance, ask the skill author for a homepage, privacy policy, or source code/SDK reference and verify the domain and API behavior before sending sensitive files.

Getting Started

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

Try saying:

• "edit my video clips"
• "export 1080p MP4"
• "trim the clip, add transitions, and"

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.

Editor on Android — Edit and Export Videos Mobile

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

A quick example: upload a 2-minute video recorded on an Android phone, type "trim the clip, add transitions, and export in 1080p", 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 significantly faster on mobile connections.

Matching Input to Actions

User prompts referencing editor on android, 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.

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

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

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.

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 clip, add transitions, and export in 1080p" → 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 clip, add transitions, and export in 1080p" — 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 Android apps and social platforms.