Instagram Video Editor Online

Skip the learning curve of professional editing software. Describe what you want — trim the clip, add a text overlay, and resize it to 9:16 for Instagram Ree...

Security Scan

The skill's declared purpose (cloud video editing) mostly matches its instructions, but there are inconsistencies and vague instructions about where it will store/read tokens and config that could lead to unexpected file access or persistent credentials—ask for clarification before installing.

Purpose & Capability

The skill claims to perform cloud-based Instagram-style video edits and requires a single credential (NEMO_TOKEN), which is coherent with using a remote video-processing API. However the YAML frontmatter in SKILL.md includes a configPaths entry (~/.config/nemovideo/) while the registry metadata at the top reported no required config paths — this mismatch is unexplained and could indicate the skill expects local config access that wasn't declared.

Instruction Scope

SKILL.md instructs the agent to interact with an external API (upload video files, create sessions, call render endpoints) which is expected. But it also instructs deriving attribution headers from the skill's frontmatter and detecting the install path (e.g., ~/.clawhub/ or ~/.cursor/skills/) to set X-Skill-Platform. That implies the agent may probe local paths or environment to determine platform and could write/save session_id and tokens without specifying where. The instructions are vague about persistent storage locations and what exactly the agent may read from disk.

Install Mechanism

No install spec and no code files — instruction-only skill. This is lower risk because nothing will be downloaded or written during installation. Runtime network calls to the external API are expected for this purpose.

Credentials

Only one required environment variable (NEMO_TOKEN) is declared, which aligns with a remote API. The SKILL.md permits generating an anonymous token and treating that value as NEMO_TOKEN; it does not clearly state how/where that token will be stored (in-memory vs persisted vs exported). The use of a config path in the frontmatter suggests possible local config access; requiring additional secrets or broad environment access is not declared but the instructions leave room for storing credentials persistently.

Persistence & Privilege

The skill does not request always:true and allows normal model invocation. Still, it tells the agent to 'Save session_id' and to use or set NEMO_TOKEN, but does not define the storage location or lifecycle. Combined with the frontmatter configPaths hint and the install-path detection behavior, there is a risk the skill will persist session/token data or read local paths without explicit declaration—this is ambiguous and should be clarified.

What to consider before installing

This skill appears to actually perform cloud video edits and only needs one API token (NEMO_TOKEN), which is reasonable. However: 1) ask the publisher to clarify where the session_id and token are stored and for how long (in-memory only or written to a file or agent config?), and whether the skill will create or read ~/.config/nemovideo/; 2) confirm whether the agent will probe local install paths (~/.clawhub/, ~/.cursor/skills/) and why—if you prefer no filesystem access, don't install; 3) verify the external API domain (mega-api-prod.nemovideo.ai) and review their privacy/retention policy before uploading sensitive videos; 4) prefer providing a disposable/limited token rather than long-lived credentials; and 5) if you need higher assurance, request the publisher add explicit statements in SKILL.md about persistence, exact headers used, and any filesystem reads/writes. These clarifications would reduce the current ambiguity and likely move the assessment toward benign.

Getting Started

Send me your video clips and I'll handle the AI video editing. Or just describe what you're after.

Try saying:

• "edit a 30-second vertical phone clip into a 1080p MP4"
• "trim the clip, add a text overlay, and resize it to 9:16 for Instagram Reels"
• "editing and formatting videos for Instagram posts and Reels for Instagram creators"

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.

Instagram Video Editor Online — Edit and Export Instagram Videos

Drop your video clips in the chat and tell me what you need. I'll handle the AI video editing on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 30-second vertical phone clip, ask for trim the clip, add a text overlay, and resize it to 9:16 for Instagram Reels, and about 30-60 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — vertical 9:16 video works perfectly for Reels and Stories without extra cropping.

Matching Input to Actions

User prompts referencing instagram video editor online, 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.

Every API call needs Authorization: Bearer <NEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is instagram-video-editor-online, 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).

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 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

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

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.

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 clip, add a text overlay, and resize it to 9:16 for Instagram Reels" → Download MP4. Takes 30-60 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "trim the clip, add a text overlay, and resize it to 9:16 for Instagram Reels" — concrete instructions get better results.

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

Export as MP4 with H.264 codec for best compatibility with Instagram uploads.