Video Editor Ai Iphone

v1.0.0

Turn a 60-second iPhone camera recording into 1080p edited iPhone videos just by typing what you need. Whether it's editing iPhone footage into polished shor...

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for susan4731-wilfordf/video-editor-ai-iphone.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Video Editor Ai Iphone" (susan4731-wilfordf/video-editor-ai-iphone) from ClawHub.
Skill page: https://clawhub.ai/susan4731-wilfordf/video-editor-ai-iphone
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Required env vars: NEMO_TOKEN
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install video-editor-ai-iphone

ClawHub CLI

Package manager switcher

npx clawhub@latest install video-editor-ai-iphone
Security Scan
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Benign
medium confidence
Purpose & Capability
The skill's name/description (AI cloud video editing for iPhone clips) matches the single required credential (NEMO_TOKEN) and the documented API endpoints for session, upload, render, and credits. Requiring an API token is expected for this service.
Instruction Scope
Runtime instructions limit activity to creating sessions, uploading user clips, sending SSE messages, polling render status, and returning download URLs — all consistent with the stated purpose. Two minor notes: (1) the skill describes deriving X-Skill-Platform from an install path (e.g., ~/.clawhub/) which implies the agent might inspect its install location; (2) instructions ask to 'keep technical details out of chat' but otherwise describe all API calls and headers. Neither is clearly malicious but they grant the agent discretion to read its environment/install context.
Install Mechanism
This is an instruction-only skill with no install spec and no code files, so it will not write or execute new binaries on disk. That is the lowest-risk install pattern.
Credentials
Only NEMO_TOKEN is declared as required, which is proportional to interacting with the nemovideo.ai APIs. However, the metadata also lists a config path (~/.config/nemovideo/) that is not referenced in the runtime instructions — an inconsistency. If implemented, reading that config path could expose local tokens or settings; the instructions do not justify that access.
Persistence & Privilege
always:false and normal autonomous invocation are used. The skill does not request unexpected persistent system privileges or attempt to modify other skills or system-wide agent settings.
Assessment
This skill appears to do what it says: it uploads clips to nemovideo.ai, runs cloud rendering, and returns a download URL. Before installing: (1) confirm you trust the NEMO_TOKEN provider and the nemovideo.ai domain; the skill will send your video files to that service (your footage leaves your device). (2) Note the metadata mentions a config path (~/.config/nemovideo/) and the instructions describe deriving headers from an install path — ask the author whether the skill will read local config or install locations and why. (3) If you don’t have a NEMO_TOKEN, the skill will obtain an anonymous token from the service (100 free credits) — be aware that this still creates an account/session on the vendor. (4) Avoid uploading sensitive footage until you’ve reviewed the vendor’s privacy policy; revoke any tokens you create if you stop using the skill.

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

📱 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk97arabdf8p9jjjwngb1ymhkt984srwg
80downloads
0stars
1versions
Updated 2w ago
v1.0.0
MIT-0

Getting Started

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

Try saying:

  • "edit my iPhone video clips"
  • "export 1080p MP4"
  • "trim the shaky parts, add transitions,"

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.

Video Editor AI iPhone — Edit iPhone Clips with AI

Drop your iPhone 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 60-second iPhone camera recording, ask for trim the shaky parts, add transitions, and export as a clean reel, 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 — iPhone MOV files upload directly — no conversion needed before processing.

Matching Input to Actions

User prompts referencing video editor ai iphone, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

User says...ActionSkip 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 video-editor-ai-iphone, 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

EventAction
Text responseApply GUI translation (§4), present to user
Tool call/resultProcess internally, don't forward
heartbeat / empty data:Keep waiting. Every 2 min: "⏳ Still working..."
Stream closesProcess 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.

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend saysYou 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

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)

Error Handling

CodeMeaningAction
0SuccessContinue
1001Bad/expired tokenRe-auth via anonymous-token (tokens expire after 7 days)
1002Session not foundNew session §3.0
2001No creditsAnonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001Unsupported fileShow supported formats
4002File too largeSuggest compress/trim
400Missing X-Client-IdGenerate Client-Id and retry (see §1)
402Free plan export blockedSubscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429Rate 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 the shaky parts, add transitions, and export as a clean reel" — concrete instructions get better results.

Max file size is 500MB. Stick to MP4, MOV, HEVC, M4V for the smoothest experience.

Export as MP4 for widest compatibility across iOS, Android, and social platforms.

Common Workflows

Quick edit: Upload → "trim the shaky parts, add transitions, and export as a clean reel" → 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.

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