Ai Video Editor Not Generator

Skip the learning curve of professional editing software. Describe what you want — cut the pauses, add transitions, and sync background music — and get edite...

Security Scan

The skill mostly describes a cloud video-editing workflow that matches its stated purpose, but there are several inconsistencies (required env var vs. auto-created anonymous token, declared config path access with no justification, unknown source/homepage) that merit caution before installing.

Purpose & Capability

The skill's name/description (AI video editor) matches the runtime instructions to upload footage, call the nemovideo.ai APIs, and download edited videos. However the registry metadata declares NEMO_TOKEN as required and lists a config path (~/.config/nemovideo/), while the SKILL.md explicitly describes generating an anonymous token at runtime if NEMO_TOKEN is not set. That mismatch (declared 'required' env vs. auto-provisioning) and the unexplained config path access are inconsistent with the simple cloud-editor purpose. Also the skill's source/homepage are unknown which reduces traceability.

Instruction Scope

Instructions routinely direct network calls to https://mega-api-prod.nemovideo.ai (auth, session creation, SSE, uploads, render start), and to upload user video/audio files — which is expected for a cloud editor. Concerning points: SKILL.md instructs creating anonymous tokens and storing session_id (but does not specify safe storage location), explicitly tells the agent to avoid displaying raw API responses or token values (which may be legitimate privacy guidance but also conceals opaque data flows), and requires three custom attribution headers that bind the agent/host to the skill. The document does not justify the declared config path but implies persistence of tokens/sessions; that gap increases risk because it's unclear what will be written/read on disk or retained.

Install Mechanism

No install spec and no code files: instruction-only skills have lower install risk because nothing is downloaded or written by an installer. All runtime actions are HTTP requests described in the SKILL.md.

Credentials

The only declared required environment variable is NEMO_TOKEN, which is appropriate for a cloud API. But SKILL.md instructs to auto-obtain an anonymous token if NEMO_TOKEN is absent, so declaring it as 'required' is misleading. The metadata also lists a config path (~/.config/nemovideo/) without explaining why filesystem access is necessary — that may indicate the skill expects to read/write tokens or session state, but this is not documented. No other unrelated secrets are requested.

Persistence & Privilege

The skill is not 'always' enabled and does not request special platform privileges; autonomous invocation is allowed (platform default). The SKILL.md implies persistent session tokens and render job IDs (and says 'store the returned session_id'), so the skill may retain state across uses. The metadata's config path suggests it might read/write config files, but the SKILL.md does not specify where or how; that ambiguity merits caution.

What to consider before installing

This skill appears to be a straightforward cloud video-editor that uploads your footage to nemovideo.ai for processing, but there are several red flags to consider before installing: - Traceability: the skill's source and homepage are unknown. Prefer integrations with a public repository or vendor page you can inspect. - Token handling: the registry marks NEMO_TOKEN as required, but the instructions will auto-create an anonymous token by POSTing to an external API if none is present. Decide whether you trust that external service with any footage you upload (the anonymous token still permits uploads and editing). - Data privacy: this skill uploads video/audio files to a third-party cloud. Do not use it with sensitive or private footage unless you accept that those files will be transmitted to and processed by mega-api-prod.nemovideo.ai. - Persistence & filesystem access: metadata lists a config path (~/.config/nemovideo/), but SKILL.md doesn't explain what it reads/writes. Ask the maintainer where session tokens and job metadata are stored and whether anything is written to disk. - Attribution headers and behavior: the skill requires extra headers that identify the skill/version/platform. That is not harmful by itself, but it ties API usage to this skill and could reveal usage patterns to the service operator. What would increase my confidence: a public source/homepage, a clear statement of where tokens/session IDs are stored (in-memory only vs. on-disk at the listed config path), and confirmation of the service's privacy/retention policy for uploaded media. If you cannot get those, treat it as higher risk and avoid uploading sensitive content.

Getting Started

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

Try saying:

• "edit a 3-minute unedited screen recording into a 1080p MP4"
• "cut the pauses, add transitions, and sync background music"
• "trimming and polishing existing footage without manual editing for content creators"

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.

AI Video Editor — Edit and Export Polished 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 3-minute unedited screen recording and want to cut the pauses, add transitions, and sync background music — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter clips under 2 minutes process noticeably faster.

Matching Input to Actions

User prompts referencing ai video editor not 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.

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	ai-video-editor-not-generator
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-detect: clawhub / cursor / unknown from install path

Every API call needs Authorization: Bearer <NEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 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

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.

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 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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "cut the pauses, add transitions, and sync background music" — concrete instructions get better results.

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

H.264 codec gives the best balance of quality and size.

Common Workflows

Quick edit: Upload → "cut the pauses, add transitions, and sync background music" → 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.