Maker Editing Generator

create raw video clips into edited video files with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators use it for generating edit...

Security Scan

The skill's requests and runtime instructions are generally consistent with a cloud video-editing service, but there are a few minor inconsistencies and behaviors you should be aware of before installing.

Purpose & Capability

Name/description describe cloud video editing and the skill only requires a single service token (NEMO_TOKEN) and references an API for uploads, sessions, and exports — these align with the stated purpose.

Instruction Scope

SKILL.md directs the agent to create sessions, upload files, run SSE interactions, poll render jobs, and fetch download URLs from the declared nemo API — all within the editing workflow. It also instructs the agent to read this file's YAML frontmatter for attribution and to detect an install path (~/.clawhub/, ~/.cursor/skills/) to set an X-Skill-Platform header; reading those local paths is outside the core edit/upload/download path but plausible for telemetry/attribution. The doc also instructs hiding technical details from the user ("Keep the technical details out of the chat"), which is a policy decision but not a technical red flag by itself.

Install Mechanism

No install spec or code files are present (instruction-only), so nothing is downloaded or written to disk by the skill itself.

Credentials

The only declared credential is NEMO_TOKEN, appropriate for a cloud video API. However, SKILL.md describes creating anonymous tokens if NEMO_TOKEN is absent and its frontmatter mentions a config path (~/.config/nemovideo/) even though the registry metadata lists no required config paths — this inconsistency should be clarified. The skill does not request unrelated credentials.

Persistence & Privilege

always:false and normal model invocation are used. The skill requires session tokens for per-job state but does not request persistent elevated privileges or modify other skills' settings.

Assessment

This skill appears to do what it claims: it talks to a nemo video API to upload clips and return edited mp4s, and it either uses a provided NEMO_TOKEN or requests an anonymous token from the service. Before installing, consider: (1) confirm you trust the remote nemo API domain (https://mega-api-prod.nemovideo.ai) because your video files and possibly metadata will be uploaded there; (2) clarify the mismatch between the registry metadata (no config paths) and the SKILL.md frontmatter which references ~/.config/nemovideo/ and install-path detection; (3) be aware the skill may read the SKILL.md frontmatter and local install-paths for attribution headers; and (4) if you do not want uploads to occur without your explicit token, require the NEMO_TOKEN and avoid allowing anonymous-token fallback. If you need higher assurance, ask the publisher for source code or a privacy/processing policy for the hosted service.

Getting Started

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

Try saying:

• "create a 2-minute raw screen recording into a 1080p MP4"
• "trim the footage, add transitions, and generate a polished intro"
• "generating edited videos from raw footage automatically 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.

Maker Editing Generator — Create and Edit Videos Fast

This tool takes your raw video clips and runs AI video creation editing through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 2-minute raw screen recording and want to trim the footage, add transitions, and generate a polished intro — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter source clips under 60 seconds process significantly faster.

Matching Input to Actions

User prompts referencing maker editing generator, 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.

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

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

• X-Skill-Source: maker-editing-generator
• 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

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

SSE Event Handling

Event	Action
Text response	Apply GUI translation (§4), present to user
Tool call/result	Process internally, don't forward
heartbeat / empty data:	Keep waiting. Every 2 min: "⏳ Still working..."
Stream closes	Process final response

~30% of editing operations return no text in the SSE stream. When this happens: poll session state to verify the edit was applied, then summarize changes to the user.

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)

Common Workflows

Quick edit: Upload → "trim the footage, add transitions, and generate a polished intro" → 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 footage, add transitions, and generate a polished intro" — 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.