Shotcut

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

Security Scan

The skill's declared purpose (cloud AI video editing) matches its runtime instructions and requested credential (NEMO_TOKEN), but there are small inconsistencies and privacy-relevant behaviors (no homepage/source, SKILL.md asks for a config path not declared in the registry, and the skill requires sending uploaded media to an external API) that warrant caution before installing.

Purpose & Capability

The name/description describe cloud AI video editing and the SKILL.md contains concrete API endpoints and upload/render workflows that align with that purpose. Requesting a single service token (NEMO_TOKEN) is appropriate. However, the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata reported none — an internal inconsistency about required config paths.

Instruction Scope

Runtime instructions stay focused on connecting to the NemoVideo backend, creating sessions, uploading user-provided media, polling render status, and returning download links. This is within the stated scope. Two items to note: (1) the skill will make network calls to obtain anonymous tokens and to upload user media (expected for a cloud editor), and (2) it instructs reading frontmatter/install path to populate X-Skill-Platform and X-Skill-Version headers — that may require inspecting agent install paths or the SKILL.md file and is a minor privacy/telemetry action.

Install Mechanism

Instruction-only skill with no install spec or code files presents low install risk — nothing is downloaded or written by an installer.

Credentials

Only one credential is declared (NEMO_TOKEN) and it's the primaryEnv, which is proportional for a cloud editing service. The SKILL.md also describes obtaining an anonymous token when NEMO_TOKEN is absent (network call). The earlier-mentioned discrepancy about a config path in the frontmatter (~/.config/nemovideo/) is unexplained and could imply the skill expects local config files or will look for them; that should have been declared explicitly.

Persistence & Privilege

The skill does not request always:true and no elevated or persistent platform privileges are requested. It uses ephemeral session tokens for cloud jobs; jobs may remain on the remote service if you close the client (not a local privilege escalation).

What to consider before installing

This skill appears to do what it says (upload your video to a NemoVideo backend, run cloud edits, return a download). Before installing or using it: (1) verify you trust the NemoVideo endpoint (no homepage or owner info is provided here), (2) understand that uploading media sends your footage to an external service — do not upload sensitive content you wouldn't want stored or processed by a third party, (3) confirm where NEMO_TOKEN comes from and whether using an anonymous token is acceptable, (4) ask the author or registry to clarify the config-path discrepancy (~/.config/nemovideo/ present in SKILL.md but not declared in registry metadata), and (5) test with non-sensitive sample videos first. If you need higher assurance, request a homepage/privacy policy or source repo before proceeding.

Getting Started

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

Try saying:

• "edit my raw video footage"
• "export 1080p MP4"
• "trim the silent parts, cut between"

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.

Shotcut — Cut and Export Edited Videos

This tool takes your raw video footage and runs AI video 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 or phone clip and want to trim the silent parts, cut between scenes, and add smooth transitions — the backend processes it in about 30-90 seconds and hands you a 1080p MP4.

Tip: shorter clips under 3 minutes process significantly faster.

Matching Input to Actions

User prompts referencing shotcut, 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: shotcut
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)

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 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

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "trim the silent parts, cut between scenes, and add smooth transitions" — concrete instructions get better results.

Max file size is 500MB. Stick to MP4, MOV, AVI, MKV for the smoothest experience.

Export as MP4 for widest compatibility across platforms.

Common Workflows

Quick edit: Upload → "trim the silent parts, cut between scenes, and add smooth transitions" → Download MP4. Takes 30-90 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.