Editor Kaise

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

Security Scan

The skill's behavior mostly matches a cloud video-editing purpose, but there are inconsistencies around claimed config paths and instructions that may read local install paths/configs and persist tokens/session state — you should review those details and the external service before installing.

Purpose & Capability

Name/description (AI cloud video editing) align with the required NEMO_TOKEN and the API endpoints in SKILL.md. However the SKILL.md metadata declares a config path (~/.config/nemovideo/) that the registry summary did not list; deriving X-Skill-Platform from local install paths also implies the skill will inspect the agent's environment/filesystem, which is beyond a minimal upload/edit tool.

Instruction Scope

Instructions tell the agent to obtain or use a NEMO_TOKEN, create sessions, upload files, use SSE, poll render status, and include custom headers. They also instruct deriving headers from YAML and detecting install path (~/.clawhub, ~/.cursor/skills/) which requires reading local filesystem/context. The skill asks to 'store the returned session_id' and not to surface raw tokens — the storage location is unspecified (memory vs disk), creating ambiguity about persistence and local writes.

Install Mechanism

Instruction-only skill with no install spec and no code files — nothing is downloaded or written by an install step, which minimizes immediate install-time risk.

Credentials

Only one credential (NEMO_TOKEN) is declared as required, which is appropriate for a remote editing service. But the SKILL.md both declares a config path (~/.config/nemovideo/) and instructs auto-generating/storing a token if NEMO_TOKEN is absent; it's unclear whether the skill will write tokens to disk or elsewhere. The agent may also read install paths to set headers — that is additional environment access not justified in detail by the description.

Persistence & Privilege

always: false (good). The skill instructs storing session_id and obtaining a 7-day anonymous token if none is present. There is no explicit instruction to modify other skills or system settings, but the unspecified storage location for tokens/session IDs and the declared configPath imply potential on-disk persistence — clarify where tokens/sessions are stored before installing.

What to consider before installing

This skill implements a cloud-based video editor that uploads your files to a remote service (mega-api-prod.nemovideo.ai) and requires a NEMO_TOKEN. Before installing: 1) Understand that any video you upload will be sent to that external service — don’t upload private/sensitive footage unless you trust their policies. 2) Clarify where the skill will store the anonymous token and session_id (in memory vs a file under ~/.config/nemovideo/). The SKILL.md suggests it may read your install path and config directory to populate headers — if you prefer the skill not to inspect or write local files, ask the author to document and limit that behavior. 3) If you want tighter control, set NEMO_TOKEN yourself (so it doesn't auto-generate and persist) and confirm whether the skill will write any files. These inconsistencies (declared config path vs registry metadata, and unspecified token/session storage) are the primary reasons this is flagged as suspicious.

Getting Started

Got raw video clips to work with? Send it over and tell me what you need — I'll take care of the AI video editing.

Try saying:

• "edit a 2-minute unedited phone recording into a 1080p MP4"
• "trim unnecessary parts, add transitions, and export as a clean video"
• "editing raw footage into a polished video without manual skills for beginner creators and students"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer <token>, Content-Type: application/json, and body {"task_name":"project","language":"<detected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

Editor Kaise — Edit and Export Clean Videos

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

A quick example: upload a 2-minute unedited phone recording, type "trim unnecessary parts, add transitions, and export as a clean video", 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.

Matching Input to Actions

User prompts referencing editor kaise, 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is editor-kaise, X-Skill-Version comes from the version field, and X-Skill-Platform is detected from the install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, otherwise unknown).

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

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.

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.

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)

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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "trim unnecessary parts, add transitions, and export as a clean video" — 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.

Common Workflows

Quick edit: Upload → "trim unnecessary parts, add transitions, and export as a clean video" → 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.